EROS Main Image File: A Picture Perfect Database for Landsat Imagery and Aerial Photography.

ERIC Educational Resources Information Center

Jack, Robert F.

1984-01-01

Describes Earth Resources Observation System online database, which provides access to computerized images of Earth obtained via satellite. Highlights include retrieval system and commands, types of images, search strategies, other online functions, and interpretation of accessions. Satellite information, sources and samples of accessions, and…

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.

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

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

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

Using an image-extended relational database to support content-based image retrieval in a PACS.

PubMed

Traina, Caetano; Traina, Agma J M; Araújo, Myrian R B; Bueno, Josiane M; Chino, Fabio J T; Razente, Humberto; Azevedo-Marques, Paulo M

2005-12-01

This paper presents a new Picture Archiving and Communication System (PACS), called cbPACS, which has content-based image retrieval capabilities. The cbPACS answers range and k-nearest- neighbor similarity queries, employing a relational database manager extended to support images. The images are compared through their features, which are extracted by an image-processing module and stored in the extended relational database. The database extensions were developed aiming at efficiently answering similarity queries by taking advantage of specialized indexing methods. The main concept supporting the extensions is the definition, inside the relational manager, of distance functions based on features extracted from the images. An extension to the SQL language enables the construction of an interpreter that intercepts the extended commands and translates them to standard SQL, allowing any relational database server to be used. By now, the system implemented works on features based on color distribution of the images through normalized histograms as well as metric histograms. Metric histograms are invariant regarding scale, translation and rotation of images and also to brightness transformations. The cbPACS is prepared to integrate new image features, based on texture and shape of the main objects in the image.

Image-guided decision support system for pulmonary nodule classification in 3D thoracic CT images

NASA Astrophysics Data System (ADS)

Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kusumoto, Masahiro; Kakinuma, Ryutaro; Mori, Kiyoshi; Yamada, Kozo; Nishiyama, Hiroyuki; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

2004-05-01

The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of pulmonary nodules. This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional (3-D) CT image database of pulmonary nodules for which diagnosis is known. In order to build the system, there are following issues that should be solved: 1) to categorize the nodule database with respect to morphological and internal features, 2) to quickly search nodule images similar to an indeterminate nodule from a large database, and 3) to reveal malignancy likelihood computed by using similar nodule images. Especially, the first problem influences the design of other issues. The successful categorization of nodule pattern might lead physicians to find important cues that characterize benign and malignant nodules. This paper focuses on an approach to categorize the nodule database with respect to nodule shape and CT density patterns inside nodule.

An image database management system for conducting CAD research

NASA Astrophysics Data System (ADS)

Gruszauskas, Nicholas; Drukker, Karen; Giger, Maryellen L.

2007-03-01

The development of image databases for CAD research is not a trivial task. The collection and management of images and their related metadata from multiple sources is a time-consuming but necessary process. By standardizing and centralizing the methods in which these data are maintained, one can generate subsets of a larger database that match the specific criteria needed for a particular research project in a quick and efficient manner. A research-oriented management system of this type is highly desirable in a multi-modality CAD research environment. An online, webbased database system for the storage and management of research-specific medical image metadata was designed for use with four modalities of breast imaging: screen-film mammography, full-field digital mammography, breast ultrasound and breast MRI. The system was designed to consolidate data from multiple clinical sources and provide the user with the ability to anonymize the data. Input concerning the type of data to be stored as well as desired searchable parameters was solicited from researchers in each modality. The backbone of the database was created using MySQL. A robust and easy-to-use interface for entering, removing, modifying and searching information in the database was created using HTML and PHP. This standardized system can be accessed using any modern web-browsing software and is fundamental for our various research projects on computer-aided detection, diagnosis, cancer risk assessment, multimodality lesion assessment, and prognosis. Our CAD database system stores large amounts of research-related metadata and successfully generates subsets of cases that match the user's desired search criteria.

The UBIRIS.v2: a database of visible wavelength iris images captured on-the-move and at-a-distance.

PubMed

Proença, Hugo; Filipe, Sílvio; Santos, Ricardo; Oliveira, João; Alexandre, Luís A

2010-08-01

The iris is regarded as one of the most useful traits for biometric recognition and the dissemination of nationwide iris-based recognition systems is imminent. However, currently deployed systems rely on heavy imaging constraints to capture near infrared images with enough quality. Also, all of the publicly available iris image databases contain data correspondent to such imaging constraints and therefore are exclusively suitable to evaluate methods thought to operate on these type of environments. The main purpose of this paper is to announce the availability of the UBIRIS.v2 database, a multisession iris images database which singularly contains data captured in the visible wavelength, at-a-distance (between four and eight meters) and on on-the-move. This database is freely available for researchers concerned about visible wavelength iris recognition and will be useful in accessing the feasibility and specifying the constraints of this type of biometric recognition.

Informatics in radiology: use of CouchDB for document-based storage of DICOM objects.

PubMed

Rascovsky, Simón J; Delgado, Jorge A; Sanz, Alexander; Calvo, Víctor D; Castrillón, Gabriel

2012-01-01

Picture archiving and communication systems traditionally have depended on schema-based Structured Query Language (SQL) databases for imaging data management. To optimize database size and performance, many such systems store a reduced set of Digital Imaging and Communications in Medicine (DICOM) metadata, discarding informational content that might be needed in the future. As an alternative to traditional database systems, document-based key-value stores recently have gained popularity. These systems store documents containing key-value pairs that facilitate data searches without predefined schemas. Document-based key-value stores are especially suited to archive DICOM objects because DICOM metadata are highly heterogeneous collections of tag-value pairs conveying specific information about imaging modalities, acquisition protocols, and vendor-supported postprocessing options. The authors used an open-source document-based database management system (Apache CouchDB) to create and test two such databases; CouchDB was selected for its overall ease of use, capability for managing attachments, and reliance on HTTP and Representational State Transfer standards for accessing and retrieving data. A large database was created first in which the DICOM metadata from 5880 anonymized magnetic resonance imaging studies (1,949,753 images) were loaded by using a Ruby script. To provide the usual DICOM query functionality, several predefined "views" (standard queries) were created by using JavaScript. For performance comparison, the same queries were executed in both the CouchDB database and a SQL-based DICOM archive. The capabilities of CouchDB for attachment management and database replication were separately assessed in tests of a similar, smaller database. Results showed that CouchDB allowed efficient storage and interrogation of all DICOM objects; with the use of information retrieval algorithms such as map-reduce, all the DICOM metadata stored in the large database were searchable with only a minimal increase in retrieval time over that with the traditional database management system. Results also indicated possible uses for document-based databases in data mining applications such as dose monitoring, quality assurance, and protocol optimization. RSNA, 2012

Distributed data collection for a database of radiological image interpretations

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Ostchega, Yechiam; Goh, Gin-Hua; Thoma, George R.

1997-01-01

The National Library of Medicine, in collaboration with the National Center for Health Statistics and the National Institute for Arthritis and Musculoskeletal and Skin Diseases, has built a system for collecting radiological interpretations for a large set of x-ray images acquired as part of the data gathered in the second National Health and Nutrition Examination Survey. This system is capable of delivering across the Internet 5- and 10-megabyte x-ray images to Sun workstations equipped with X Window based 2048 X 2560 image displays, for the purpose of having these images interpreted for the degree of presence of particular osteoarthritic conditions in the cervical and lumbar spines. The collected interpretations can then be stored in a database at the National Library of Medicine, under control of the Illustra DBMS. This system is a client/server database application which integrates (1) distributed server processing of client requests, (2) a customized image transmission method for faster Internet data delivery, (3) distributed client workstations with high resolution displays, image processing functions and an on-line digital atlas, and (4) relational database management of the collected data.

A database system to support image algorithm evaluation

NASA Technical Reports Server (NTRS)

Lien, Y. E.

1977-01-01

The design is given of an interactive image database system IMDB, which allows the user to create, retrieve, store, display, and manipulate images through the facility of a high-level, interactive image query (IQ) language. The query language IQ permits the user to define false color functions, pixel value transformations, overlay functions, zoom functions, and windows. The user manipulates the images through generic functions. The user can direct images to display devices for visual and qualitative analysis. Image histograms and pixel value distributions can also be computed to obtain a quantitative analysis of images.

Autonomous facial recognition system inspired by human visual system based logarithmical image visualization technique

NASA Astrophysics Data System (ADS)

Wan, Qianwen; Panetta, Karen; Agaian, Sos

2017-05-01

Autonomous facial recognition system is widely used in real-life applications, such as homeland border security, law enforcement identification and authentication, and video-based surveillance analysis. Issues like low image quality, non-uniform illumination as well as variations in poses and facial expressions can impair the performance of recognition systems. To address the non-uniform illumination challenge, we present a novel robust autonomous facial recognition system inspired by the human visual system based, so called, logarithmical image visualization technique. In this paper, the proposed method, for the first time, utilizes the logarithmical image visualization technique coupled with the local binary pattern to perform discriminative feature extraction for facial recognition system. The Yale database, the Yale-B database and the ATT database are used for computer simulation accuracy and efficiency testing. The extensive computer simulation demonstrates the method's efficiency, accuracy, and robustness of illumination invariance for facial recognition.

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.

Microvax-based data management and reduction system for the regional planetary image facilities

NASA Technical Reports Server (NTRS)

Arvidson, R.; Guinness, E.; Slavney, S.; Weiss, B.

1987-01-01

Presented is a progress report for the Regional Planetary Image Facilities (RPIF) prototype image data management and reduction system being jointly implemented by Washington University and the USGS, Flagstaff. The system will consist of a MicroVAX with a high capacity (approx 300 megabyte) disk drive, a compact disk player, an image display buffer, a videodisk player, USGS image processing software, and SYSTEM 1032 - a commercial relational database management package. The USGS, Flagstaff, will transfer their image processing software including radiometric and geometric calibration routines, to the MicroVAX environment. Washington University will have primary responsibility for developing the database management aspects of the system and for integrating the various aspects into a working system.

Laptop Computer - Based Facial Recognition System Assessment

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

R. A. Cain; G. B. Singleton

2001-03-01

The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results.more » After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master operating in remote locations. Remote users could perform real-time searches where network connectivity is not available. As images are enrolled at the remote locations, periodic database synchronization is necessary.« less

Image database for digital hand atlas

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Dey, Partha S.; Gertych, Arkadiusz; Pospiech-Kurkowska, Sywia

2003-05-01

Bone age assessment is a procedure frequently performed in pediatric patients to evaluate their growth disorder. A commonly used method is atlas matching by a visual comparison of a hand radiograph with a small reference set of old Greulich-Pyle atlas. We have developed a new digital hand atlas with a large set of clinically normal hand images of diverse ethnic groups. In this paper, we will present our system design and implementation of the digital atlas database to support the computer-aided atlas matching for bone age assessment. The system consists of a hand atlas image database, a computer-aided diagnostic (CAD) software module for image processing and atlas matching, and a Web user interface. Users can use a Web browser to push DICOM images, directly or indirectly from PACS, to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, are then extracted and compared with patterns from the atlas image database to assess the bone age. The digital atlas method built on a large image database and current Internet technology provides an alternative to supplement or replace the traditional one for a quantitative, accurate and cost-effective assessment of bone age.

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.

Exploring the feasibility of traditional image querying tasks for industrial radiographs

NASA Astrophysics Data System (ADS)

Bray, Iliana E.; Tsai, Stephany J.; Jimenez, Edward S.

2015-08-01

Although there have been great strides in object recognition with optical images (photographs), there has been comparatively little research into object recognition for X-ray radiographs. Our exploratory work contributes to this area by creating an object recognition system designed to recognize components from a related database of radiographs. Object recognition for radiographs must be approached differently than for optical images, because radiographs have much less color-based information to distinguish objects, and they exhibit transmission overlap that alters perceived object shapes. The dataset used in this work contained more than 55,000 intermixed radiographs and photographs, all in a compressed JPEG form and with multiple ways of describing pixel information. For this work, a robust and efficient system is needed to combat problems presented by properties of the X-ray imaging modality, the large size of the given database, and the quality of the images contained in said database. We have explored various pre-processing techniques to clean the cluttered and low-quality images in the database, and we have developed our object recognition system by combining multiple object detection and feature extraction methods. We present the preliminary results of the still-evolving hybrid object recognition system.

Mass-storage management for distributed image/video archives

NASA Astrophysics Data System (ADS)

Franchi, Santina; Guarda, Roberto; Prampolini, Franco

1993-04-01

The realization of image/video database requires a specific design for both database structures and mass storage management. This issue has addressed the project of the digital image/video database system that has been designed at IBM SEMEA Scientific & Technical Solution Center. Proper database structures have been defined to catalog image/video coding technique with the related parameters, and the description of image/video contents. User workstations and servers are distributed along a local area network. Image/video files are not managed directly by the DBMS server. Because of their wide size, they are stored outside the database on network devices. The database contains the pointers to the image/video files and the description of the storage devices. The system can use different kinds of storage media, organized in a hierarchical structure. Three levels of functions are available to manage the storage resources. The functions of the lower level provide media management. They allow it to catalog devices and to modify device status and device network location. The medium level manages image/video files on a physical basis. It manages file migration between high capacity media and low access time media. The functions of the upper level work on image/video file on a logical basis, as they archive, move and copy image/video data selected by user defined queries. These functions are used to support the implementation of a storage management strategy. The database information about characteristics of both storage devices and coding techniques are used by the third level functions to fit delivery/visualization requirements and to reduce archiving costs.

[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.

Astronomical data analysis software and systems I; Proceedings of the 1st Annual Conference, Tucson, AZ, Nov. 6-8, 1991

NASA Technical Reports Server (NTRS)

Worrall, Diana M. (Editor); Biemesderfer, Chris (Editor); Barnes, Jeannette (Editor)

1992-01-01

Consideration is given to a definition of a distribution format for X-ray data, the Einstein on-line system, the NASA/IPAC extragalactic database, COBE astronomical databases, Cosmic Background Explorer astronomical databases, the ADAM software environment, the Groningen Image Processing System, search for a common data model for astronomical data analysis systems, deconvolution for real and synthetic apertures, pitfalls in image reconstruction, a direct method for spectral and image restoration, and a discription of a Poisson imagery super resolution algorithm. Also discussed are multivariate statistics on HI and IRAS images, a faint object classification using neural networks, a matched filter for improving SNR of radio maps, automated aperture photometry of CCD images, interactive graphics interpreter, the ROSAT extreme ultra-violet sky survey, a quantitative study of optimal extraction, an automated analysis of spectra, applications of synthetic photometry, an algorithm for extra-solar planet system detection and data reduction facilities for the William Herschel telescope.

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.

SU-E-J-129: A Strategy to Consolidate the Image Database of a VERO Unit Into a Radiotherapy Management System

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

Yan, Y; Medin, P; Yordy, J

2014-06-01

Purpose: To present a strategy to integrate the imaging database of a VERO unit with a treatment management system (TMS) to improve clinical workflow and consolidate image data to facilitate clinical quality control and documentation. Methods: A VERO unit is equipped with both kV and MV imaging capabilities for IGRT treatments. It has its own imaging database behind a firewall. It has been a challenge to transfer images on this unit to a TMS in a radiation therapy clinic so that registered images can be reviewed remotely with an approval or rejection record. In this study, a software system, iPump-VERO,more » was developed to connect VERO and a TMS in our clinic. The patient database folder on the VERO unit was mapped to a read-only folder on a file server outside VERO firewall. The application runs on a regular computer with the read access to the patient database folder. It finds the latest registered images and fuses them in one of six predefined patterns before sends them via DICOM connection to the TMS. The residual image registration errors will be overlaid on the fused image to facilitate image review. Results: The fused images of either registered kV planar images or CBCT images are fully DICOM compatible. A sentinel module is built to sense new registered images with negligible computing resources from the VERO ExacTrac imaging computer. It takes a few seconds to fuse registered images and send them to the TMS. The whole process is automated without any human intervention. Conclusion: Transferring images in DICOM connection is the easiest way to consolidate images of various sources in your TMS. Technically the attending does not have to go to the VERO treatment console to review image registration prior delivery. It is a useful tool for a busy clinic with a VERO unit.« less

A database for spectral image quality

NASA Astrophysics Data System (ADS)

Le Moan, Steven; George, Sony; Pedersen, Marius; Blahová, Jana; Hardeberg, Jon Yngve

2015-01-01

We introduce a new image database dedicated to multi-/hyperspectral image quality assessment. A total of nine scenes representing pseudo-at surfaces of different materials (textile, wood, skin. . . ) were captured by means of a 160 band hyperspectral system with a spectral range between 410 and 1000nm. Five spectral distortions were designed, applied to the spectral images and subsequently compared in a psychometric experiment, in order to provide a basis for applications such as the evaluation of spectral image difference measures. The database can be downloaded freely from http://www.colourlab.no/cid.

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.

Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo

NASA Astrophysics Data System (ADS)

Kohigashi, Satoru; Nakamae, Koji; Fujioka, Hiromu

2005-04-01

We develop the image based computer assisted diagnosis system for benign paroxysmal positional vertigo (BPPV) that consists of the balance control system simulator, the 3D eye movement simulator, and the extraction method of nystagmus response directly from an eye movement image sequence. In the system, the causes and conditions of BPPV are estimated by searching the database for record matching with the nystagmus response for the observed eye image sequence of the patient with BPPV. The database includes the nystagmus responses for simulated eye movement sequences. The eye movement velocity is obtained by using the balance control system simulator that allows us to simulate BPPV under various conditions such as canalithiasis, cupulolithiasis, number of otoconia, otoconium size, and so on. Then the eye movement image sequence is displayed on the CRT by the 3D eye movement simulator. The nystagmus responses are extracted from the image sequence by the proposed method and are stored in the database. In order to enhance the diagnosis accuracy, the nystagmus response for a newly simulated sequence is matched with that for the observed sequence. From the matched simulation conditions, the causes and conditions of BPPV are estimated. We apply our image based computer assisted diagnosis system to two real eye movement image sequences for patients with BPPV to show its validity.

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.

Trainable Cataloging for Digital Image Libraries with Applications to Volcano Detection

NASA Technical Reports Server (NTRS)

Burl, M. C.; Fayyad, U. M.; Perona, P.; Smyth, P.

1995-01-01

Users of digital image libraries are often not interested in image data per se but in derived products such as catalogs of objects of interest. Converting an image database into a usable catalog is typically carried out manually at present. For many larger image databases the purely manual approach is completely impractical. In this paper we describe the development of a trainable cataloging system: the user indicates the location of the objects of interest for a number of training images and the system learns to detect and catalog these objects in the rest of the database. In particular we describe the application of this system to the cataloging of small volcanoes in radar images of Venus. The volcano problem is of interest because of the scale (30,000 images, order of 1 million detectable volcanoes), technical difficulty (the variability of the volcanoes in appearance) and the scientific importance of the problem. The problem of uncertain or subjective ground truth is of fundamental importance in cataloging problems of this nature and is discussed in some detail. Experimental results are presented which quantify and compare the detection performance of the system relative to human detection performance. The paper concludes by discussing the limitations of the proposed system and the lessons learned of general relevance to the development of digital image libraries.

An automated system for terrain database construction

NASA Technical Reports Server (NTRS)

Johnson, L. F.; Fretz, R. K.; Logan, T. L.; Bryant, N. A.

1987-01-01

An automated Terrain Database Preparation System (TDPS) for the construction and editing of terrain databases used in computerized wargaming simulation exercises has been developed. The TDPS system operates under the TAE executive, and it integrates VICAR/IBIS image processing and Geographic Information System software with CAD/CAM data capture and editing capabilities. The terrain database includes such features as roads, rivers, vegetation, and terrain roughness.

Programmed database system at the Chang Gung Craniofacial Center: part II--digitizing photographs.

PubMed

Chuang, Shiow-Shuh; Hung, Kai-Fong; de Villa, Glenda H; Chen, Philip K T; Lo, Lun-Jou; Chang, Sophia C N; Yu, Chung-Chih; Chen, Yu-Ray

2003-07-01

The archival tools used for digital images in advertising are not to fulfill the clinic requisition and are just beginning to develop. The storage of a large amount of conventional photographic slides needs a lot of space and special conditions. In spite of special precautions, degradation of the slides still occurs. The most common degradation is the appearance of fungus flecks. With the recent advances in digital technology, it is now possible to store voluminous numbers of photographs on a computer hard drive and keep them for a long time. A self-programmed interface has been developed to integrate database and image browser system that can build and locate needed files archive in a matter of seconds with the click of a button. This system requires hardware and software were market provided. There are 25,200 patients recorded in the database that involve 24,331 procedures. In the image files, there are 6,384 patients with 88,366 digital pictures files. From 1999 through 2002, NT400,000 dollars have been saved using the new system. Photographs can be managed with the integrating Database and Browse software for database archiving. This allows labeling of the individual photographs with demographic information and browsing. Digitized images are not only more efficient and economical than the conventional slide images, but they also facilitate clinical studies.

Automatic image database generation from CAD for 3D object recognition

NASA Astrophysics Data System (ADS)

Sardana, Harish K.; Daemi, Mohammad F.; Ibrahim, Mohammad K.

1993-06-01

The development and evaluation of Multiple-View 3-D object recognition systems is based on a large set of model images. Due to the various advantages of using CAD, it is becoming more and more practical to use existing CAD data in computer vision systems. Current PC- level CAD systems are capable of providing physical image modelling and rendering involving positional variations in cameras, light sources etc. We have formulated a modular scheme for automatic generation of various aspects (views) of the objects in a model based 3-D object recognition system. These views are generated at desired orientations on the unit Gaussian sphere. With a suitable network file sharing system (NFS), the images can directly be stored on a database located on a file server. This paper presents the image modelling solutions using CAD in relation to multiple-view approach. Our modular scheme for data conversion and automatic image database storage for such a system is discussed. We have used this approach in 3-D polyhedron recognition. An overview of the results, advantages and limitations of using CAD data and conclusions using such as scheme are also presented.

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.

Animal Detection in Natural Images: Effects of Color and Image Database

PubMed Central

Zhu, Weina; Drewes, Jan; Gegenfurtner, Karl R.

2013-01-01

The visual system has a remarkable ability to extract categorical information from complex natural scenes. In order to elucidate the role of low-level image features for the recognition of objects in natural scenes, we recorded saccadic eye movements and event-related potentials (ERPs) in two experiments, in which human subjects had to detect animals in previously unseen natural images. We used a new natural image database (ANID) that is free of some of the potential artifacts that have plagued the widely used COREL images. Color and grayscale images picked from the ANID and COREL databases were used. In all experiments, color images induced a greater N1 EEG component at earlier time points than grayscale images. We suggest that this influence of color in animal detection may be masked by later processes when measuring reation times. The ERP results of go/nogo and forced choice tasks were similar to those reported earlier. The non-animal stimuli induced bigger N1 than animal stimuli both in the COREL and ANID databases. This result indicates ultra-fast processing of animal images is possible irrespective of the particular database. With the ANID images, the difference between color and grayscale images is more pronounced than with the COREL images. The earlier use of the COREL images might have led to an underestimation of the contribution of color. Therefore, we conclude that the ANID image database is better suited for the investigation of the processing of natural scenes than other databases commonly used. PMID:24130744

A complete database for the Einstein imaging proportional counter

NASA Technical Reports Server (NTRS)

Helfand, David J.

1991-01-01

A complete database for the Einstein Imaging Proportional Counter (IPC) was completed. The original data that makes up the archive is described as well as the structure of the database, the Op-Ed analysis system, the technical advances achieved relative to the analysis of (IPC) data, the data products produced, and some uses to which the database has been put by scientists outside Columbia University over the past year.

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

NASA Astrophysics Data System (ADS)

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

1996-03-01

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

LIPS database with LIPService: a microscopic image database of intracellular structures in Arabidopsis guard cells.

PubMed

Higaki, Takumi; Kutsuna, Natsumaro; Hasezawa, Seiichiro

2013-05-16

Intracellular configuration is an important feature of cell status. Recent advances in microscopic imaging techniques allow us to easily obtain a large number of microscopic images of intracellular structures. In this circumstance, automated microscopic image recognition techniques are of extreme importance to future phenomics/visible screening approaches. However, there was no benchmark microscopic image dataset for intracellular organelles in a specified plant cell type. We previously established the Live Images of Plant Stomata (LIPS) database, a publicly available collection of optical-section images of various intracellular structures of plant guard cells, as a model system of environmental signal perception and transduction. Here we report recent updates to the LIPS database and the establishment of a database table, LIPService. We updated the LIPS dataset and established a new interface named LIPService to promote efficient inspection of intracellular structure configurations. Cell nuclei, microtubules, actin microfilaments, mitochondria, chloroplasts, endoplasmic reticulum, peroxisomes, endosomes, Golgi bodies, and vacuoles can be filtered using probe names or morphometric parameters such as stomatal aperture. In addition to the serial optical sectional images of the original LIPS database, new volume-rendering data for easy web browsing of three-dimensional intracellular structures have been released to allow easy inspection of their configurations or relationships with cell status/morphology. We also demonstrated the utility of the new LIPS image database for automated organelle recognition of images from another plant cell image database with image clustering analyses. The updated LIPS database provides a benchmark image dataset for representative intracellular structures in Arabidopsis guard cells. The newly released LIPService allows users to inspect the relationship between organellar three-dimensional configurations and morphometrical parameters.

Image Format Conversion to DICOM and Lookup Table Conversion to Presentation Value of the Japanese Society of Radiological Technology (JSRT) Standard Digital Image Database.

PubMed

Yanagita, Satoshi; Imahana, Masato; Suwa, Kazuaki; Sugimura, Hitomi; Nishiki, Masayuki

2016-01-01

Japanese Society of Radiological Technology (JSRT) standard digital image database contains many useful cases of chest X-ray images, and has been used in many state-of-the-art researches. However, the pixel values of all the images are simply digitized as relative density values by utilizing a scanned film digitizer. As a result, the pixel values are completely different from the standardized display system input value of digital imaging and communications in medicine (DICOM), called presentation value (P-value), which can maintain a visual consistency when observing images using different display luminance. Therefore, we converted all the images from JSRT standard digital image database to DICOM format followed by the conversion of the pixel values to P-value using an original program developed by ourselves. Consequently, JSRT standard digital image database has been modified so that the visual consistency of images is maintained among different luminance displays.

Federated Web-accessible Clinical Data Management within an Extensible NeuroImaging Database

PubMed Central

Keator, David B.; Wei, Dingying; Fennema-Notestine, Christine; Pease, Karen R.; Bockholt, Jeremy; Grethe, Jeffrey S.

2010-01-01

Managing vast datasets collected throughout multiple clinical imaging communities has become critical with the ever increasing and diverse nature of datasets. Development of data management infrastructure is further complicated by technical and experimental advances that drive modifications to existing protocols and acquisition of new types of research data to be incorporated into existing data management systems. In this paper, an extensible data management system for clinical neuroimaging studies is introduced: The Human Clinical Imaging Database (HID) and Toolkit. The database schema is constructed to support the storage of new data types without changes to the underlying schema. The complex infrastructure allows management of experiment data, such as image protocol and behavioral task parameters, as well as subject-specific data, including demographics, clinical assessments, and behavioral task performance metrics. Of significant interest, embedded clinical data entry and management tools enhance both consistency of data reporting and automatic entry of data into the database. The Clinical Assessment Layout Manager (CALM) allows users to create on-line data entry forms for use within and across sites, through which data is pulled into the underlying database via the generic clinical assessment management engine (GAME). Importantly, the system is designed to operate in a distributed environment, serving both human users and client applications in a service-oriented manner. Querying capabilities use a built-in multi-database parallel query builder/result combiner, allowing web-accessible queries within and across multiple federated databases. The system along with its documentation is open-source and available from the Neuroimaging Informatics Tools and Resource Clearinghouse (NITRC) site. PMID:20567938

Stereoscopic wide field of view imaging system

NASA Technical Reports Server (NTRS)

Prechtl, Eric F. (Inventor); Sedwick, Raymond J. (Inventor); Jonas, Eric M. (Inventor)

2011-01-01

A stereoscopic imaging system incorporates a plurality of imaging devices or cameras to generate a high resolution, wide field of view image database from which images can be combined in real time to provide wide field of view or panoramic or omni-directional still or video images.

Computer-aided system for detecting runway incursions

NASA Astrophysics Data System (ADS)

Sridhar, Banavar; Chatterji, Gano B.

1994-07-01

A synthetic vision system for enhancing the pilot's ability to navigate and control the aircraft on the ground is described. The system uses the onboard airport database and images acquired by external sensors. Additional navigation information needed by the system is provided by the Inertial Navigation System and the Global Positioning System. The various functions of the system, such as image enhancement, map generation, obstacle detection, collision avoidance, guidance, etc., are identified. The available technologies, some of which were developed at NASA, that are applicable to the aircraft ground navigation problem are noted. Example images of a truck crossing the runway while the aircraft flies close to the runway centerline are described. These images are from a sequence of images acquired during one of the several flight experiments conducted by NASA to acquire data to be used for the development and verification of the synthetic vision concepts. These experiments provide a realistic database including video and infrared images, motion states from the Inertial Navigation System and the Global Positioning System, and camera parameters.

Spatial and symbolic queries for 3D image data

NASA Astrophysics Data System (ADS)

Benson, Daniel C.; Zick, Gregory L.

1992-04-01

We present a query system for an object-oriented biomedical imaging database containing 3-D anatomical structures and their corresponding 2-D images. The graphical interface facilitates the formation of spatial queries, nonspatial or symbolic queries, and combined spatial/symbolic queries. A query editor is used for the creation and manipulation of 3-D query objects as volumes, surfaces, lines, and points. Symbolic predicates are formulated through a combination of text fields and multiple choice selections. Query results, which may include images, image contents, composite objects, graphics, and alphanumeric data, are displayed in multiple views. Objects returned by the query may be selected directly within the views for further inspection or modification, or for use as query objects in subsequent queries. Our image database query system provides visual feedback and manipulation of spatial query objects, multiple views of volume data, and the ability to combine spatial and symbolic queries. The system allows for incremental enhancement of existing objects and the addition of new objects and spatial relationships. The query system is designed for databases containing symbolic and spatial data. This paper discuses its application to data acquired in biomedical 3- D image reconstruction, but it is applicable to other areas such as CAD/CAM, geographical information systems, and computer vision.

Image query and indexing for digital x rays

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Thoma, George R.

1998-12-01

The web-based medical information retrieval system (WebMIRS) allows interned access to databases containing 17,000 digitized x-ray spine images and associated text data from National Health and Nutrition Examination Surveys (NHANES). WebMIRS allows SQL query of the text, and viewing of the returned text records and images using a standard browser. We are now working (1) to determine utility of data directly derived from the images in our databases, and (2) to investigate the feasibility of computer-assisted or automated indexing of the images to support image retrieval of images of interest to biomedical researchers in the field of osteoarthritis. To build an initial database based on image data, we are manually segmenting a subset of the vertebrae, using techniques from vertebral morphometry. From this, we will derive and add to the database vertebral features. This image-derived data will enhance the user's data access capability by enabling the creation of combined SQL/image-content queries.

Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors

PubMed Central

Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

2017-01-01

Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods. PMID:28587269

Convolutional Neural Network-Based Finger-Vein Recognition Using NIR Image Sensors.

PubMed

Hong, Hyung Gil; Lee, Min Beom; Park, Kang Ryoung

2017-06-06

Conventional finger-vein recognition systems perform recognition based on the finger-vein lines extracted from the input images or image enhancement, and texture feature extraction from the finger-vein images. In these cases, however, the inaccurate detection of finger-vein lines lowers the recognition accuracy. In the case of texture feature extraction, the developer must experimentally decide on a form of the optimal filter for extraction considering the characteristics of the image database. To address this problem, this research proposes a finger-vein recognition method that is robust to various database types and environmental changes based on the convolutional neural network (CNN). In the experiments using the two finger-vein databases constructed in this research and the SDUMLA-HMT finger-vein database, which is an open database, the method proposed in this research showed a better performance compared to the conventional methods.

SU-E-T-255: Development of a Michigan Quality Assurance (MQA) Database for Clinical Machine Operations

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

Roberts, D

Purpose: A unified database system was developed to allow accumulation, review and analysis of quality assurance (QA) data for measurement, treatment, imaging and simulation equipment in our department. Recording these data in a database allows a unified and structured approach to review and analysis of data gathered using commercial database tools. Methods: A clinical database was developed to track records of quality assurance operations on linear accelerators, a computed tomography (CT) scanner, high dose rate (HDR) afterloader and imaging systems such as on-board imaging (OBI) and Calypso in our department. The database was developed using Microsoft Access database and visualmore » basic for applications (VBA) programming interface. Separate modules were written for accumulation, review and analysis of daily, monthly and annual QA data. All modules were designed to use structured query language (SQL) as the basis of data accumulation and review. The SQL strings are dynamically re-written at run time. The database also features embedded documentation, storage of documents produced during QA activities and the ability to annotate all data within the database. Tests are defined in a set of tables that define test type, specific value, and schedule. Results: Daily, Monthly and Annual QA data has been taken in parallel with established procedures to test MQA. The database has been used to aggregate data across machines to examine the consistency of machine parameters and operations within the clinic for several months. Conclusion: The MQA application has been developed as an interface to a commercially available SQL engine (JET 5.0) and a standard database back-end. The MQA system has been used for several months for routine data collection.. The system is robust, relatively simple to extend and can be migrated to a commercial SQL server.« less

A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

PubMed

Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

2015-01-01

The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

Palmprint Based Verification System Using SURF Features

NASA Astrophysics Data System (ADS)

Srinivas, Badrinath G.; Gupta, Phalguni

This paper describes the design and development of a prototype of robust biometric system for verification. The system uses features extracted using Speeded Up Robust Features (SURF) operator of human hand. The hand image for features is acquired using a low cost scanner. The palmprint region extracted is robust to hand translation and rotation on the scanner. The system is tested on IITK database of 200 images and PolyU database of 7751 images. The system is found to be robust with respect to translation and rotation. It has FAR 0.02%, FRR 0.01% and accuracy of 99.98% and can be a suitable system for civilian applications and high-security environments.

Basic level scene understanding: categories, attributes and structures

PubMed Central

Xiao, Jianxiong; Hays, James; Russell, Bryan C.; Patterson, Genevieve; Ehinger, Krista A.; Torralba, Antonio; Oliva, Aude

2013-01-01

A longstanding goal of computer vision is to build a system that can automatically understand a 3D scene from a single image. This requires extracting semantic concepts and 3D information from 2D images which can depict an enormous variety of environments that comprise our visual world. This paper summarizes our recent efforts toward these goals. First, we describe the richly annotated SUN database which is a collection of annotated images spanning 908 different scene categories with object, attribute, and geometric labels for many scenes. This database allows us to systematically study the space of scenes and to establish a benchmark for scene and object recognition. We augment the categorical SUN database with 102 scene attributes for every image and explore attribute recognition. Finally, we present an integrated system to extract the 3D structure of the scene and objects depicted in an image. PMID:24009590

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

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.

Design and Implementation of CNEOST Image Database Based on NoSQL System

NASA Astrophysics Data System (ADS)

Wang, X.

2013-07-01

The China Near Earth Object Survey Telescope (CNEOST) is the largest Schmidt telescope in China, and it has acquired more than 3 TB astronomical image data since it saw the first light in 2006. After the upgradation of the CCD camera in 2013, over 10 TB data will be obtained every year. The management of massive images is not only an indispensable part of data processing pipeline but also the basis of data sharing. Based on the analysis of requirement, an image management system is designed and implemented by employing the non-relational database.

Design and Implementation of CNEOST Image Database Based on NoSQL System

NASA Astrophysics Data System (ADS)

Wang, Xin

2014-04-01

The China Near Earth Object Survey Telescope is the largest Schmidt telescope in China, and it has acquired more than 3 TB astronomical image data since it saw the first light in 2006. After the upgrade of the CCD camera in 2013, over 10 TB data will be obtained every year. The management of the massive images is not only an indispensable part of data processing pipeline but also the basis of data sharing. Based on the analysis of requirement, an image management system is designed and implemented by employing the non-relational database.

A data model and database for high-resolution pathology analytical image informatics.

PubMed

Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

2011-01-01

The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming increasingly feasible for basic, clinical, and translational research studies to produce thousands of whole-slide images. Systematic analysis of these large datasets requires efficient data management support for representing and indexing results from hundreds of interrelated analyses generating very large volumes of quantifications such as shape and texture and of classifications of the quantified features. We have designed a data model and a database to address the data management requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines. The data model represents virtual slide related image, annotation, markup and feature information. The database supports a wide range of metadata and spatial queries on images, annotations, markups, and features. We currently have three databases running on a Dell PowerEdge T410 server with CentOS 5.5 Linux operating system. The database server is IBM DB2 Enterprise Edition 9.7.2. The set of databases consists of 1) a TMA database containing image analysis results from 4740 cases of breast cancer, with 641 MB storage size; 2) an algorithm validation database, which stores markups and annotations from two segmentation algorithms and two parameter sets on 18 selected slides, with 66 GB storage size; and 3) an in silico brain tumor study database comprising results from 307 TCGA slides, with 365 GB storage size. The latter two databases also contain human-generated annotations and markups for regions and nuclei. Modeling and managing pathology image analysis results in a database provide immediate benefits on the value and usability of data in a research study. The database provides powerful query capabilities, which are otherwise difficult or cumbersome to support by other approaches such as programming languages. Standardized, semantic annotated data representation and interfaces also make it possible to more efficiently share image data and analysis results.

Interactive Scene Analysis Module - A sensor-database fusion system for telerobotic environments

NASA Technical Reports Server (NTRS)

Cooper, Eric G.; Vazquez, Sixto L.; Goode, Plesent W.

1992-01-01

Accomplishing a task with telerobotics typically involves a combination of operator control/supervision and a 'script' of preprogrammed commands. These commands usually assume that the location of various objects in the task space conform to some internal representation (database) of that task space. The ability to quickly and accurately verify the task environment against the internal database would improve the robustness of these preprogrammed commands. In addition, the on-line initialization and maintenance of a task space database is difficult for operators using Cartesian coordinates alone. This paper describes the Interactive Scene' Analysis Module (ISAM) developed to provide taskspace database initialization and verification utilizing 3-D graphic overlay modelling, video imaging, and laser radar based range imaging. Through the fusion of taskspace database information and image sensor data, a verifiable taskspace model is generated providing location and orientation data for objects in a task space. This paper also describes applications of the ISAM in the Intelligent Systems Research Laboratory (ISRL) at NASA Langley Research Center, and discusses its performance relative to representation accuracy and operator interface efficiency.

Digital hand atlas and computer-aided bone age assessment via the Web

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente

1999-07-01

A frequently used assessment method of bone age is atlas matching by a radiological examination of a hand image against a reference set of atlas patterns of normal standards. We are in a process of developing a digital hand atlas with a large standard set of normal hand and wrist images that reflect the skeletal maturity, race and sex difference, and current child development. The digital hand atlas will be used for a computer-aided bone age assessment via Web. We have designed and partially implemented a computer-aided diagnostic (CAD) system for Web-based bone age assessment. The system consists of a digital hand atlas, a relational image database and a Web-based user interface. The digital atlas is based on a large standard set of normal hand an wrist images with extracted bone objects and quantitative features. The image database uses a content- based indexing to organize the hand images and their attributes and present to users in a structured way. The Web-based user interface allows users to interact with the hand image database from browsers. Users can use a Web browser to push a clinical hand image to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, will be extracted and compared with patterns from the atlas database to assess the bone age. The relevant reference imags and the final assessment report will be sent back to the user's browser via Web. The digital atlas will remove the disadvantages of the currently out-of-date one and allow the bone age assessment to be computerized and done conveniently via Web. In this paper, we present the system design and Web-based client-server model for computer-assisted bone age assessment and our initial implementation of the digital atlas database.

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.

DIGITAL CARTOGRAPHY OF THE PLANETS: NEW METHODS, ITS STATUS, AND ITS FUTURE.

USGS Publications Warehouse

Batson, R.M.

1987-01-01

A system has been developed that establishes a standardized cartographic database for each of the 19 planets and major satellites that have been explored to date. Compilation of the databases involves both traditional and newly developed digital image processing and mosaicking techniques, including radiometric and geometric corrections of the images. Each database, or digital image model (DIM), is a digital mosaic of spacecraft images that have been radiometrically and geometrically corrected and photometrically modeled. During compilation, ancillary data files such as radiometric calibrations and refined photometric values for all camera lens and filter combinations and refined camera-orientation matrices for all images used in the mapping are produced.

Advanced Land Imager Assessment System

NASA Technical Reports Server (NTRS)

Chander, Gyanesh; Choate, Mike; Christopherson, Jon; Hollaren, Doug; Morfitt, Ron; Nelson, Jim; Nelson, Shar; Storey, James; Helder, Dennis; Ruggles, Tim;

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

PubMed

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

2017-09-01

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

Automated search and retrieval of information from imaged documents using optical correlation techniques

NASA Astrophysics Data System (ADS)

Stalcup, Bruce W.; Dennis, Phillip W.; Dydyk, Robert B.

1999-10-01

Litton PRC and Litton Data Systems Division are developing a system, the Imaged Document Optical Correlation and Conversion System (IDOCCS), to provide a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provides the search and retrieval of information from imaged documents. IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited; e.g., imaged documents containing an agency's seal or logo can be singled out. In this paper, we present a description of IDOCCS as well as preliminary performance results and theoretical projections.

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

NASA Astrophysics Data System (ADS)

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

2001-12-01

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

Multimedia Database at National Museum of Ethnology

NASA Astrophysics Data System (ADS)

Sugita, Shigeharu

This paper describes the information management system at National Museum of Ethnology, Osaka, Japan. This museum is a kind of research center for cultural anthropology, and has many computer systems such as IBM 3090, VAX11/780, Fujitu M340R, etc. With these computers, distributed multimedia databases are constructed in which not only bibliographic data but also artifact image, slide image, book page image, etc. are stored. The number of data is now about 1.3 million items. These data can be retrieved and displayed on the multimedia workstation which has several displays.

Digital map databases in support of avionic display systems

NASA Astrophysics Data System (ADS)

Trenchard, Michael E.; Lohrenz, Maura C.; Rosche, Henry, III; Wischow, Perry B.

1991-08-01

The emergence of computerized mission planning systems (MPS) and airborne digital moving map systems (DMS) has necessitated the development of a global database of raster aeronautical chart data specifically designed for input to these systems. The Naval Oceanographic and Atmospheric Research Laboratory''s (NOARL) Map Data Formatting Facility (MDFF) is presently dedicated to supporting these avionic display systems with the development of the Compressed Aeronautical Chart (CAC) database on Compact Disk Read Only Memory (CDROM) optical discs. The MDFF is also developing a series of aircraft-specific Write-Once Read Many (WORM) optical discs. NOARL has initiated a comprehensive research program aimed at improving the pilots'' moving map displays current research efforts include the development of an alternate image compression technique and generation of a standard set of color palettes. The CAC database will provide digital aeronautical chart data in six different scales. CAC is derived from the Defense Mapping Agency''s (DMA) Equal Arc-second (ARC) Digitized Raster Graphics (ADRG) a series of scanned aeronautical charts. NOARL processes ADRG to tailor the chart image resolution to that of the DMS display while reducing storage requirements through image compression techniques. CAC is being distributed by DMA as a library of CDROMs.

The clinical information system GastroBase: integration of image processing and laboratory communication.

PubMed

Kocna, P

1995-01-01

GastroBase, a clinical information system, incorporates patient identification, medical records, images, laboratory data, patient history, physical examination, and other patient-related information. Program modules are written in C; all data is processed using Novell-Btrieve data manager. Patient identification database represents the main core of this information systems. A graphic library developed in the past year and graphic modules with a special video-card enables the storing, archiving, and linking of different images to the electronic patient-medical-record. GastroBase has been running for more than four years in daily routine and the database contains more than 25,000 medical records and 1,500 images. This new version of GastroBase is now incorporated into the clinical information system of University Clinic in Prague.

Identification of suitable fundus images using automated quality assessment methods.

PubMed

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

2014-04-01

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

Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.

PubMed

Messay, Temesguen; Hardie, Russell C; Tuinstra, Timothy R

2015-05-01

We present new pulmonary nodule segmentation algorithms for computed tomography (CT). These include a fully-automated (FA) system, a semi-automated (SA) system, and a hybrid system. Like most traditional systems, the new FA system requires only a single user-supplied cue point. On the other hand, the SA system represents a new algorithm class requiring 8 user-supplied control points. This does increase the burden on the user, but we show that the resulting system is highly robust and can handle a variety of challenging cases. The proposed hybrid system starts with the FA system. If improved segmentation results are needed, the SA system is then deployed. The FA segmentation engine has 2 free parameters, and the SA system has 3. These parameters are adaptively determined for each nodule in a search process guided by a regression neural network (RNN). The RNN uses a number of features computed for each candidate segmentation. We train and test our systems using the new Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) data. To the best of our knowledge, this is one of the first nodule-specific performance benchmarks using the new LIDC-IDRI dataset. We also compare the performance of the proposed methods with several previously reported results on the same data used by those other methods. Our results suggest that the proposed FA system improves upon the state-of-the-art, and the SA system offers a considerable boost over the FA system. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Information mining in remote sensing imagery

NASA Astrophysics Data System (ADS)

Li, Jiang

The volume of remotely sensed imagery continues to grow at an enormous rate due to the advances in sensor technology, and our capability for collecting and storing images has greatly outpaced our ability to analyze and retrieve information from the images. This motivates us to develop image information mining techniques, which is very much an interdisciplinary endeavor drawing upon expertise in image processing, databases, information retrieval, machine learning, and software design. This dissertation proposes and implements an extensive remote sensing image information mining (ReSIM) system prototype for mining useful information implicitly stored in remote sensing imagery. The system consists of three modules: image processing subsystem, database subsystem, and visualization and graphical user interface (GUI) subsystem. Land cover and land use (LCLU) information corresponding to spectral characteristics is identified by supervised classification based on support vector machines (SVM) with automatic model selection, while textural features that characterize spatial information are extracted using Gabor wavelet coefficients. Within LCLU categories, textural features are clustered using an optimized k-means clustering approach to acquire search efficient space. The clusters are stored in an object-oriented database (OODB) with associated images indexed in an image database (IDB). A k-nearest neighbor search is performed using a query-by-example (QBE) approach. Furthermore, an automatic parametric contour tracing algorithm and an O(n) time piecewise linear polygonal approximation (PLPA) algorithm are developed for shape information mining of interesting objects within the image. A fuzzy object-oriented database based on the fuzzy object-oriented data (FOOD) model is developed to handle the fuzziness and uncertainty. Three specific applications are presented: integrated land cover and texture pattern mining, shape information mining for change detection of lakes, and fuzzy normalized difference vegetation index (NDVI) pattern mining. The study results show the effectiveness of the proposed system prototype and the potentials for other applications in remote sensing.

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.

Training system for digital mammographic diagnoses of breast cancer

NASA Astrophysics Data System (ADS)

Thomaz, R. L.; Nirschl Crozara, M. G.; Patrocinio, A. C.

2013-03-01

As the technology evolves, the analog mammography systems are being replaced by digital systems. The digital system uses video monitors as the display of mammographic images instead of the previously used screen-film and negatoscope for analog images. The change in the way of visualizing mammographic images may require a different approach for training the health care professionals in diagnosing the breast cancer with digital mammography. Thus, this paper presents a computational approach to train the health care professionals providing a smooth transition between analog and digital technology also training to use the advantages of digital image processing tools to diagnose the breast cancer. This computational approach consists of a software where is possible to open, process and diagnose a full mammogram case from a database, which has the digital images of each of the mammographic views. The software communicates with a gold standard digital mammogram cases database. This database contains the digital images in Tagged Image File Format (TIFF) and the respective diagnoses according to BI-RADSTM, these files are read by software and shown to the user as needed. There are also some digital image processing tools that can be used to provide better visualization of each single image. The software was built based on a minimalist and a user-friendly interface concept that might help in the smooth transition. It also has an interface for inputting diagnoses from the professional being trained, providing a result feedback. This system has been already completed, but hasn't been applied to any professional training yet.

Open source database of images DEIMOS: extension for large-scale subjective image quality assessment

NASA Astrophysics Data System (ADS)

Vítek, Stanislav

2014-09-01

DEIMOS (Database of Images: Open Source) is an open-source database of images and video sequences for testing, verification and comparison of various image and/or video processing techniques such as compression, reconstruction and enhancement. This paper deals with extension of the database allowing performing large-scale web-based subjective image quality assessment. Extension implements both administrative and client interface. The proposed system is aimed mainly at mobile communication devices, taking into account advantages of HTML5 technology; it means that participants don't need to install any application and assessment could be performed using web browser. The assessment campaign administrator can select images from the large database and then apply rules defined by various test procedure recommendations. The standard test procedures may be fully customized and saved as a template. Alternatively the administrator can define a custom test, using images from the pool and other components, such as evaluating forms and ongoing questionnaires. Image sequence is delivered to the online client, e.g. smartphone or tablet, as a fully automated assessment sequence or viewer can decide on timing of the assessment if required. Environmental data and viewing conditions (e.g. illumination, vibrations, GPS coordinates, etc.), may be collected and subsequently analyzed.

A Mobile Food Record For Integrated Dietary Assessment*

PubMed Central

Ahmad, Ziad; Kerr, Deborah A.; Bosch, Marc; Boushey, Carol J.; Delp, Edward J.; Khanna, Nitin; Zhu, Fengqing

2017-01-01

This paper presents an integrated dietary assessment system based on food image analysis that uses mobile devices or smartphones. We describe two components of our integrated system: a mobile application and an image-based food nutrient database that is connected to the mobile application. An easy-to-use mobile application user interface is described that was designed based on user preferences as well as the requirements of the image analysis methods. The user interface is validated by user feedback collected from several studies. Food nutrient and image databases are also described which facilitates image-based dietary assessment and enable dietitians and other healthcare professionals to monitor patients dietary intake in real-time. The system has been tested and validated in several user studies involving more than 500 users who took more than 60,000 food images under controlled and community-dwelling conditions. PMID:28691119

Digital hand atlas for web-based bone age assessment: system design and implementation

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente

2000-04-01

A frequently used assessment method of skeletal age is atlas matching by a radiological examination of a hand image against a small set of Greulich-Pyle patterns of normal standards. The method however can lead to significant deviation in age assessment, due to a variety of observers with different levels of training. The Greulich-Pyle atlas based on middle upper class white populations in the 1950s, is also not fully applicable for children of today, especially regarding the standard development in other racial groups. In this paper, we present our system design and initial implementation of a digital hand atlas and computer-aided diagnostic (CAD) system for Web-based bone age assessment. The digital atlas will remove the disadvantages of the currently out-of-date one and allow the bone age assessment to be computerized and done conveniently via Web. The system consists of a hand atlas database, a CAD module and a Java-based Web user interface. The atlas database is based on a large set of clinically normal hand images of diverse ethnic groups. The Java-based Web user interface allows users to interact with the hand image database form browsers. Users can use a Web browser to push a clinical hand image to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, is then extracted and compared with patterns from the atlas database to assess the bone age.

SparCLeS: dynamic l₁ sparse classifiers with level sets for robust beard/moustache detection and segmentation.

PubMed

Le, T Hoang Ngan; Luu, Khoa; Savvides, Marios

2013-08-01

Robust facial hair detection and segmentation is a highly valued soft biometric attribute for carrying out forensic facial analysis. In this paper, we propose a novel and fully automatic system, called SparCLeS, for beard/moustache detection and segmentation in challenging facial images. SparCLeS uses the multiscale self-quotient (MSQ) algorithm to preprocess facial images and deal with illumination variation. Histogram of oriented gradients (HOG) features are extracted from the preprocessed images and a dynamic sparse classifier is built using these features to classify a facial region as either containing skin or facial hair. A level set based approach, which makes use of the advantages of both global and local information, is then used to segment the regions of a face containing facial hair. Experimental results demonstrate the effectiveness of our proposed system in detecting and segmenting facial hair regions in images drawn from three databases, i.e., the NIST Multiple Biometric Grand Challenge (MBGC) still face database, the NIST Color Facial Recognition Technology FERET database, and the Labeled Faces in the Wild (LFW) database.

Federated web-accessible clinical data management within an extensible neuroimaging database.

PubMed

Ozyurt, I Burak; Keator, David B; Wei, Dingying; Fennema-Notestine, Christine; Pease, Karen R; Bockholt, Jeremy; Grethe, Jeffrey S

2010-12-01

Managing vast datasets collected throughout multiple clinical imaging communities has become critical with the ever increasing and diverse nature of datasets. Development of data management infrastructure is further complicated by technical and experimental advances that drive modifications to existing protocols and acquisition of new types of research data to be incorporated into existing data management systems. In this paper, an extensible data management system for clinical neuroimaging studies is introduced: The Human Clinical Imaging Database (HID) and Toolkit. The database schema is constructed to support the storage of new data types without changes to the underlying schema. The complex infrastructure allows management of experiment data, such as image protocol and behavioral task parameters, as well as subject-specific data, including demographics, clinical assessments, and behavioral task performance metrics. Of significant interest, embedded clinical data entry and management tools enhance both consistency of data reporting and automatic entry of data into the database. The Clinical Assessment Layout Manager (CALM) allows users to create on-line data entry forms for use within and across sites, through which data is pulled into the underlying database via the generic clinical assessment management engine (GAME). Importantly, the system is designed to operate in a distributed environment, serving both human users and client applications in a service-oriented manner. Querying capabilities use a built-in multi-database parallel query builder/result combiner, allowing web-accessible queries within and across multiple federated databases. The system along with its documentation is open-source and available from the Neuroimaging Informatics Tools and Resource Clearinghouse (NITRC) site.

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.

A digital library for medical imaging activities

NASA Astrophysics Data System (ADS)

dos Santos, Marcelo; Furuie, Sérgio S.

2007-03-01

This work presents the development of an electronic infrastructure to make available a free, online, multipurpose and multimodality medical image database. The proposed infrastructure implements a distributed architecture for medical image database, authoring tools, and a repository for multimedia documents. Also it includes a peer-reviewed model that assures quality of dataset. This public repository provides a single point of access for medical images and related information to facilitate retrieval tasks. The proposed approach has been used as an electronic teaching system in Radiology as well.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

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

Fish Karyome: A karyological information network database of Indian Fishes.

PubMed

Nagpure, Naresh Sahebrao; Pathak, Ajey Kumar; Pati, Rameshwar; Singh, Shri Prakash; Singh, Mahender; Sarkar, Uttam Kumar; Kushwaha, Basdeo; Kumar, Ravindra

2012-01-01

'Fish Karyome', a database on karyological information of Indian fishes have been developed that serves as central source for karyotype data about Indian fishes compiled from the published literature. Fish Karyome has been intended to serve as a liaison tool for the researchers and contains karyological information about 171 out of 2438 finfish species reported in India and is publically available via World Wide Web. The database provides information on chromosome number, morphology, sex chromosomes, karyotype formula and cytogenetic markers etc. Additionally, it also provides the phenotypic information that includes species name, its classification, and locality of sample collection, common name, local name, sex, geographical distribution, and IUCN Red list status. Besides, fish and karyotype images, references for 171 finfish species have been included in the database. Fish Karyome has been developed using SQL Server 2008, a relational database management system, Microsoft's ASP.NET-2008 and Macromedia's FLASH Technology under Windows 7 operating environment. The system also enables users to input new information and images into the database, search and view the information and images of interest using various search options. Fish Karyome has wide range of applications in species characterization and identification, sex determination, chromosomal mapping, karyo-evolution and systematics of fishes.

GPCALMA: A Tool For Mammography With A GRID-Connected Distributed Database

NASA Astrophysics Data System (ADS)

Bottigli, U.; Cerello, P.; Cheran, S.; Delogu, P.; Fantacci, M. E.; Fauci, F.; Golosio, B.; Lauria, A.; Lopez Torres, E.; Magro, R.; Masala, G. L.; Oliva, P.; Palmiero, R.; Raso, G.; Retico, A.; Stumbo, S.; Tangaro, S.

2003-09-01

The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN (National Institute of Nuclear Physics) sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed database of digitised mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) software which is integrated in a station that can also be used to acquire new images, as archive and to perform statistical analysis. The images (18×24 cm2, digitised by a CCD linear scanner with a 85 μm pitch and 4096 gray levels) are completely described: pathological ones have a consistent characterization with radiologist's diagnosis and histological data, non pathological ones correspond to patients with a follow up at least three years. The distributed database is realized throught the connection of all the hospitals and research centers in GRID tecnology. In each hospital local patients digital images are stored in the local database. Using GRID connection, GPCALMA will allow each node to work on distributed database data as well as local database data. Using its database the GPCALMA tools perform several analysis. A texture analysis, i.e. an automated classification on adipose, dense or glandular texture, can be provided by the system. GPCALMA software also allows classification of pathological features, in particular massive lesions (both opacities and spiculated lesions) analysis and microcalcification clusters analysis. The detection of pathological features is made using neural network software that provides a selection of areas showing a given "suspicion level" of lesion occurrence. The performance of the GPCALMA system will be presented in terms of the ROC (Receiver Operating Characteristic) curves. The results of GPCALMA system as "second reader" will also be presented.

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

Red Lesion Detection Using Dynamic Shape Features for Diabetic Retinopathy Screening.

PubMed

Seoud, Lama; Hurtut, Thomas; Chelbi, Jihed; Cheriet, Farida; Langlois, J M Pierre

2016-04-01

The development of an automatic telemedicine system for computer-aided screening and grading of diabetic retinopathy depends on reliable detection of retinal lesions in fundus images. In this paper, a novel method for automatic detection of both microaneurysms and hemorrhages in color fundus images is described and validated. The main contribution is a new set of shape features, called Dynamic Shape Features, that do not require precise segmentation of the regions to be classified. These features represent the evolution of the shape during image flooding and allow to discriminate between lesions and vessel segments. The method is validated per-lesion and per-image using six databases, four of which are publicly available. It proves to be robust with respect to variability in image resolution, quality and acquisition system. On the Retinopathy Online Challenge's database, the method achieves a FROC score of 0.420 which ranks it fourth. On the Messidor database, when detecting images with diabetic retinopathy, the proposed method achieves an area under the ROC curve of 0.899, comparable to the score of human experts, and it outperforms state-of-the-art approaches.

Interactive searching of facial image databases

NASA Astrophysics Data System (ADS)

Nicholls, Robert A.; Shepherd, John W.; Shepherd, Jean

1995-09-01

A set of psychological facial descriptors has been devised to enable computerized searching of criminal photograph albums. The descriptors have been used to encode image databased of up to twelve thousand images. Using a system called FACES, the databases are searched by translating a witness' verbal description into corresponding facial descriptors. Trials of FACES have shown that this coding scheme is more productive and efficient than searching traditional photograph albums. An alternative method of searching the encoded database using a genetic algorithm is currenly being tested. The genetic search method does not require the witness to verbalize a description of the target but merely to indicate a degree of similarity between the target and a limited selection of images from the database. The major drawback of FACES is that is requires a manual encoding of images. Research is being undertaken to automate the process, however, it will require an algorithm which can predict human descriptive values. Alternatives to human derived coding schemes exist using statistical classifications of images. Since databases encoded using statistical classifiers do not have an obvious direct mapping to human derived descriptors, a search method which does not require the entry of human descriptors is required. A genetic search algorithm is being tested for such a purpose.

EROS main image file - A picture perfect database for Landsat imagery and aerial photography

NASA Technical Reports Server (NTRS)

Jack, R. F.

1984-01-01

The Earth Resources Observation System (EROS) Program was established by the U.S. Department of the Interior in 1966 under the administration of the Geological Survey. It is primarily concerned with the application of remote sensing techniques for the management of natural resources. The retrieval system employed to search the EROS database is called INORAC (Inquiry, Ordering, and Accounting). A description is given of the types of images identified in EROS, taking into account Landsat imagery, Skylab images, Gemini/Apollo photography, and NASA aerial photography. Attention is given to retrieval commands, geographic coordinate searching, refinement techniques, various online functions, and questions regarding the access to the EROS Main Image File.

Interactive Radiology teaching file system: the development of a MIRC-compliant and user-centered e-learning resource.

PubMed

dos-Santos, M; Fujino, A

2012-01-01

Radiology teaching usually employs a systematic and comprehensive set of medical images and related information. Databases with representative radiological images and documents are highly desirable and widely used in Radiology teaching programs. Currently, computer-based teaching file systems are widely used in Medicine and Radiology teaching as an educational resource. This work addresses a user-centered radiology electronic teaching file system as an instance of MIRC compliant medical image database. Such as a digital library, the clinical cases are available to access by using a web browser. The system has offered great opportunities to some Radiology residents interact with experts. This has been done by applying user-centered techniques and creating usage context-based tools in order to make available an interactive system.

Navigation integrity monitoring and obstacle detection for enhanced-vision systems

NASA Astrophysics Data System (ADS)

Korn, Bernd; Doehler, Hans-Ullrich; Hecker, Peter

2001-08-01

Typically, Enhanced Vision (EV) systems consist of two main parts, sensor vision and synthetic vision. Synthetic vision usually generates a virtual out-the-window view using databases and accurate navigation data, e. g. provided by differential GPS (DGPS). The reliability of the synthetic vision highly depends on both, the accuracy of the used database and the integrity of the navigation data. But especially in GPS based systems, the integrity of the navigation can't be guaranteed. Furthermore, only objects that are stored in the database can be displayed to the pilot. Consequently, unexpected obstacles are invisible and this might cause severe problems. Therefore, additional information has to be extracted from sensor data to overcome these problems. In particular, the sensor data analysis has to identify obstacles and has to monitor the integrity of databases and navigation. Furthermore, if a lack of integrity arises, navigation data, e.g. the relative position of runway and aircraft, has to be extracted directly from the sensor data. The main contribution of this paper is about the realization of these three sensor data analysis tasks within our EV system, which uses the HiVision 35 GHz MMW radar of EADS, Ulm as the primary EV sensor. For the integrity monitoring, objects extracted from radar images are registered with both database objects and objects (e. g. other aircrafts) transmitted via data link. This results in a classification into known and unknown radar image objects and consequently, in a validation of the integrity of database and navigation. Furthermore, special runway structures are searched for in the radar image where they should appear. The outcome of this runway check contributes to the integrity analysis, too. Concurrent to this investigation a radar image based navigation is performed without using neither precision navigation nor detailed database information to determine the aircraft's position relative to the runway. The performance of our approach is demonstrated with real data acquired during extensive flight tests to several airports in Northern Germany.

TheHiveDB image data management and analysis framework.

PubMed

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-06

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative.

TheHiveDB image data management and analysis framework

PubMed Central

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-01

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative. PMID:24432000

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.

Effective spatial database support for acquiring spatial information from remote sensing images

NASA Astrophysics Data System (ADS)

Jin, Peiquan; Wan, Shouhong; Yue, Lihua

2009-12-01

In this paper, a new approach to maintain spatial information acquiring from remote-sensing images is presented, which is based on Object-Relational DBMS. According to this approach, the detected and recognized results of targets are stored and able to be further accessed in an ORDBMS-based spatial database system, and users can access the spatial information using the standard SQL interface. This approach is different from the traditional ArcSDE-based method, because the spatial information management module is totally integrated into the DBMS and becomes one of the core modules in the DBMS. We focus on three issues, namely the general framework for the ORDBMS-based spatial database system, the definitions of the add-in spatial data types and operators, and the process to develop a spatial Datablade on Informix. The results show that the ORDBMS-based spatial database support for image-based target detecting and recognition is easy and practical to be implemented.

Vision based flight procedure stereo display system

NASA Astrophysics Data System (ADS)

Shen, Xiaoyun; Wan, Di; Ma, Lan; He, Yuncheng

2008-03-01

A virtual reality flight procedure vision system is introduced in this paper. The digital flight map database is established based on the Geographic Information System (GIS) and high definitions satellite remote sensing photos. The flight approaching area database is established through computer 3D modeling system and GIS. The area texture is generated from the remote sensing photos and aerial photographs in various level of detail. According to the flight approaching procedure, the flight navigation information is linked to the database. The flight approaching area vision can be dynamic displayed according to the designed flight procedure. The flight approaching area images are rendered in 2 channels, one for left eye images and the others for right eye images. Through the polarized stereoscopic projection system, the pilots and aircrew can get the vivid 3D vision of the flight destination approaching area. Take the use of this system in pilots preflight preparation procedure, the aircrew can get more vivid information along the flight destination approaching area. This system can improve the aviator's self-confidence before he carries out the flight mission, accordingly, the flight safety is improved. This system is also useful in validate the visual flight procedure design, and it helps to the flight procedure design.

QBIC project: querying images by content, using color, texture, and shape

NASA Astrophysics Data System (ADS)

Niblack, Carlton W.; Barber, Ron; Equitz, Will; Flickner, Myron D.; Glasman, Eduardo H.; Petkovic, Dragutin; Yanker, Peter; Faloutsos, Christos; Taubin, Gabriel

1993-04-01

In the query by image content (QBIC) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical (`Give me other images that contain a tumor with a texture like this one'), photo-journalism (`Give me images that have blue at the top and red at the bottom'), and many others in art, fashion, cataloging, retailing, and industry. Key issues include derivation and computation of attributes of images and objects that provide useful query functionality, retrieval methods based on similarity as opposed to exact match, query by image example or user drawn image, the user interfaces, query refinement and navigation, high dimensional database indexing, and automatic and semi-automatic database population. We currently have a prototype system written in X/Motif and C running on an RS/6000 that allows a variety of queries, and a test database of over 1000 images and 1000 objects populated from commercially available photo clip art images. In this paper we present the main algorithms for color texture, shape and sketch query that we use, show example query results, and discuss future directions.

Study on parallel and distributed management of RS data based on spatial database

NASA Astrophysics Data System (ADS)

Chen, Yingbiao; Qian, Qinglan; Wu, Hongqiao; Liu, Shijin

2009-10-01

With the rapid development of current earth-observing technology, RS image data storage, management and information publication become a bottle-neck for its appliance and popularization. There are two prominent problems in RS image data storage and management system. First, background server hardly handle the heavy process of great capacity of RS data which stored at different nodes in a distributing environment. A tough burden has put on the background server. Second, there is no unique, standard and rational organization of Multi-sensor RS data for its storage and management. And lots of information is lost or not included at storage. Faced at the above two problems, the paper has put forward a framework for RS image data parallel and distributed management and storage system. This system aims at RS data information system based on parallel background server and a distributed data management system. Aiming at the above two goals, this paper has studied the following key techniques and elicited some revelatory conclusions. The paper has put forward a solid index of "Pyramid, Block, Layer, Epoch" according to the properties of RS image data. With the solid index mechanism, a rational organization for different resolution, different area, different band and different period of Multi-sensor RS image data is completed. In data storage, RS data is not divided into binary large objects to be stored at current relational database system, while it is reconstructed through the above solid index mechanism. A logical image database for the RS image data file is constructed. In system architecture, this paper has set up a framework based on a parallel server of several common computers. Under the framework, the background process is divided into two parts, the common WEB process and parallel process.

The design and implementation of image query system based on color feature

NASA Astrophysics Data System (ADS)

Yao, Xu-Dong; Jia, Da-Chun; Li, Lin

2013-07-01

ASP.NET technology was used to construct the B/S mode image query system. The theory and technology of database design, color feature extraction from image, index and retrieval in the construction of the image repository were researched. The campus LAN and WAN environment were used to test the system. From the test results, the needs of user queries about related resources were achieved by system architecture design.

An open access thyroid ultrasound image database

NASA Astrophysics Data System (ADS)

Pedraza, Lina; Vargas, Carlos; Narváez, Fabián.; Durán, Oscar; Muñoz, Emma; Romero, Eduardo

2015-01-01

Computer aided diagnosis systems (CAD) have been developed to assist radiologists in the detection and diagnosis of abnormalities and a large number of pattern recognition techniques have been proposed to obtain a second opinion. Most of these strategies have been evaluated using different datasets making their performance incomparable. In this work, an open access database of thyroid ultrasound images is presented. The dataset consists of a set of B-mode Ultrasound images, including a complete annotation and diagnostic description of suspicious thyroid lesions by expert radiologists. Several types of lesions as thyroiditis, cystic nodules, adenomas and thyroid cancers were included while an accurate lesion delineation is provided in XML format. The diagnostic description of malignant lesions was confirmed by biopsy. The proposed new database is expected to be a resource for the community to assess different CAD systems.

A proposed computer diagnostic system for malignant melanoma (CDSMM).

PubMed

Shao, S; Grams, R R

1994-04-01

This paper describes a computer diagnostic system for malignant melanoma. The diagnostic system is a rule base system based on image analyses and works under the PC windows environment. It consists of seven modules: I/O module, Patient/Clinic database, image processing module, classification module, rule base module and system control module. In the system, the image analyses are automatically carried out, and database management is efficient and fast. Both final clinic results and immediate results from various modules such as measured features, feature pictures and history records of the disease lesion can be presented on screen or printed out from each corresponding module or from the I/O module. The system can also work as a doctor's office-based tool to aid dermatologists with details not perceivable by the human eye. Since the system operates on a general purpose PC, it can be made portable if the I/O module is disconnected.

VIEWCACHE: An incremental pointer-based access method for autonomous interoperable databases

NASA Technical Reports Server (NTRS)

Roussopoulos, N.; Sellis, Timos

1992-01-01

One of biggest problems facing NASA today is to provide scientists efficient access to a large number of distributed databases. Our pointer-based incremental database access method, VIEWCACHE, provides such an interface for accessing distributed data sets and directories. VIEWCACHE allows database browsing and search performing inter-database cross-referencing with no actual data movement between database sites. This organization and processing is especially suitable for managing Astrophysics databases which are physically distributed all over the world. Once the search is complete, the set of collected pointers pointing to the desired data are cached. VIEWCACHE includes spatial access methods for accessing image data sets, which provide much easier query formulation by referring directly to the image and very efficient search for objects contained within a two-dimensional window. We will develop and optimize a VIEWCACHE External Gateway Access to database management systems to facilitate distributed database search.

Development and Implementation of Kumamoto Technopolis Regional Database T-KIND

NASA Astrophysics Data System (ADS)

Onoue, Noriaki

T-KIND (Techno-Kumamoto Information Network for Data-Base) is a system for effectively searching information of technology, human resources and industries which are necessary to realize Kumamoto Technopolis. It is composed of coded database, image database and LAN inside technoresearch park which is the center of R & D in the Technopolis. It constructs on-line system by networking general-purposed computers, minicomputers, optical disk file systems and so on, and provides the service through public telephone line. Two databases are now available on enterprise information and human resource information. The former covers about 4,000 enterprises, and the latter does about 2,000 persons.

An embedded face-classification system for infrared images on an FPGA

NASA Astrophysics Data System (ADS)

Soto, Javier E.; Figueroa, Miguel

2014-10-01

We present a face-classification architecture for long-wave infrared (IR) images implemented on a Field Programmable Gate Array (FPGA). The circuit is fast, compact and low power, can recognize faces in real time and be embedded in a larger image-processing and computer vision system operating locally on an IR camera. The algorithm uses Local Binary Patterns (LBP) to perform feature extraction on each IR image. First, each pixel in the image is represented as an LBP pattern that encodes the similarity between the pixel and its neighbors. Uniform LBP codes are then used to reduce the number of patterns to 59 while preserving more than 90% of the information contained in the original LBP representation. Then, the image is divided into 64 non-overlapping regions, and each region is represented as a 59-bin histogram of patterns. Finally, the algorithm concatenates all 64 regions to create a 3,776-bin spatially enhanced histogram. We reduce the dimensionality of this histogram using Linear Discriminant Analysis (LDA), which improves clustering and enables us to store an entire database of 53 subjects on-chip. During classification, the circuit applies LBP and LDA to each incoming IR image in real time, and compares the resulting feature vector to each pattern stored in the local database using the Manhattan distance. We implemented the circuit on a Xilinx Artix-7 XC7A100T FPGA and tested it with the UCHThermalFace database, which consists of 28 81 x 150-pixel images of 53 subjects in indoor and outdoor conditions. The circuit achieves a 98.6% hit ratio, trained with 16 images and tested with 12 images of each subject in the database. Using a 100 MHz clock, the circuit classifies 8,230 images per second, and consumes only 309mW.

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Quasi-real-time telemedical checkup system for x-ray examination of UGI tract based on high-speed network

NASA Astrophysics Data System (ADS)

Sakano, Toshikazu; Yamaguchi, Takahiro; Fujii, Tatsuya; Okumura, Akira; Furukawa, Isao; Ono, Sadayasu; Suzuki, Junji; Ando, Yutaka; Kohda, Ehiichi; Sugino, Yoshinori; Okada, Yoshiyuki; Amaki, Sachi

2000-05-01

We constructed a high-speed medical information network testbed, which is one of the largest testbeds in Japan, and applied it to practical medical checkups for the first time. The constructed testbed, which we call IMPACT, consists of a Super-High Definition Imaging system, a video conferencing system, a remote database system, and a 6 - 135 Mbps ATM network. The interconnected facilities include the School of Medicine in Keio University, a company's clinic, and an NTT R&D center, all in and around Tokyo. We applied IMPACT to the mass screening of the upper gastrointestinal (UGI) tract at the clinic. All 5419 radiographic images acquired at them clinic for 523 employees were digitized (2048 X 1698 X 12 bits) and transferred to a remote database in NTT. We then picked up about 50 images from five patients and sent them to nine radiological specialists at Keio University. The processing, which includes film digitization, image data transfer, and database registration, took 574 seconds per patient in average. The average reading time at Keio Univ. was 207 seconds. The overall processing time was estimated to be 781 seconds per patient. From these experimental results, we conclude that quasi-real time tele-medical checkups are possible with our prototype system.

A new phase-correlation-based iris matching for degraded images.

PubMed

Krichen, Emine; Garcia-Salicetti, Sonia; Dorizzi, Bernadette

2009-08-01

In this paper, we present a new phase-correlation-based iris matching approach in order to deal with degradations in iris images due to unconstrained acquisition procedures. Our matching system is a fusion of global and local Gabor phase-correlation schemes. The main originality of our local approach is that we do not only consider the correlation peak amplitudes but also their locations in different regions of the images. Results on several degraded databases, namely, the CASIA-BIOSECURE and Iris Challenge Evaluation 2005 databases, show the improvement of our method compared to two available reference systems, Masek and Open Source for Iris (OSRIS), in verification mode.

LONI visualization environment.

PubMed

Dinov, Ivo D; Valentino, Daniel; Shin, Bae Cheol; Konstantinidis, Fotios; Hu, Guogang; MacKenzie-Graham, Allan; Lee, Erh-Fang; Shattuck, David; Ma, Jeff; Schwartz, Craig; Toga, Arthur W

2006-06-01

Over the past decade, the use of informatics to solve complex neuroscientific problems has increased dramatically. Many of these research endeavors involve examining large amounts of imaging, behavioral, genetic, neurobiological, and neuropsychiatric data. Superimposing, processing, visualizing, or interpreting such a complex cohort of datasets frequently becomes a challenge. We developed a new software environment that allows investigators to integrate multimodal imaging data, hierarchical brain ontology systems, on-line genetic and phylogenic databases, and 3D virtual data reconstruction models. The Laboratory of Neuro Imaging visualization environment (LONI Viz) consists of the following components: a sectional viewer for imaging data, an interactive 3D display for surface and volume rendering of imaging data, a brain ontology viewer, and an external database query system. The synchronization of all components according to stereotaxic coordinates, region name, hierarchical ontology, and genetic labels is achieved via a comprehensive BrainMapper functionality, which directly maps between position, structure name, database, and functional connectivity information. This environment is freely available, portable, and extensible, and may prove very useful for neurobiologists, neurogenetisists, brain mappers, and for other clinical, pedagogical, and research endeavors.

Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

PubMed

Li, Feng

2015-07-01

This review paper is based on our research experience in the past 30 years. The importance of radiologists' role is discussed in the development or evaluation of new medical images and of computer-aided detection (CAD) schemes in chest radiology. The four main topics include (1) introducing what diseases can be included in a research database for different imaging techniques or CAD systems and what imaging database can be built by radiologists, (2) understanding how radiologists' subjective judgment can be combined with technical objective features to improve CAD performance, (3) sharing our experience in the design of successful observer performance studies, and (4) finally, discussing whether the new images and CAD systems can improve radiologists' diagnostic ability in chest radiology. In conclusion, advanced imaging techniques and detection/classification of CAD systems have a potential clinical impact on improvement of radiologists' diagnostic ability, for both the detection and the differential diagnosis of various lung diseases, in chest radiology.

Permutation coding technique for image recognition systems.

PubMed

Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

2006-11-01

A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

PubMed

Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

2016-12-01

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

An end to end secure CBIR over encrypted medical database.

PubMed

Bellafqira, Reda; Coatrieux, Gouenou; Bouslimi, Dalel; Quellec, Gwenole

2016-08-01

In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features extracted from the encrypted images are themselves encrypted. This is achieved by means of homomorphic encryption and two non-colluding servers, we however both consider as honest but curious. In that way an end to end secure CBIR process is ensured. Experimental results carried out on a diabetic retinopathy database encrypted with the Paillier cryptosystem indicate that our SCBIR achieves retrieval performance as good as if images were processed in their non-encrypted form.

An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images.

PubMed

Ahmadi, Farshid Farnood; Ebadi, Hamid

2009-01-01

3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented.

Hospital integrated parallel cluster for fast and cost-efficient image analysis: clinical experience and research evaluation

NASA Astrophysics Data System (ADS)

Erberich, Stephan G.; Hoppe, Martin; Jansen, Christian; Schmidt, Thomas; Thron, Armin; Oberschelp, Walter

2001-08-01

In the last few years more and more University Hospitals as well as private hospitals changed to digital information systems for patient record, diagnostic files and digital images. Not only that patient management becomes easier, it is also very remarkable how clinical research can profit from Picture Archiving and Communication Systems (PACS) and diagnostic databases, especially from image databases. Since images are available on the finger tip, difficulties arise when image data needs to be processed, e.g. segmented, classified or co-registered, which usually demands a lot computational power. Today's clinical environment does support PACS very well, but real image processing is still under-developed. The purpose of this paper is to introduce a parallel cluster of standard distributed systems and its software components and how such a system can be integrated into a hospital environment. To demonstrate the cluster technique we present our clinical experience with the crucial but cost-intensive motion correction of clinical routine and research functional MRI (fMRI) data, as it is processed in our Lab on a daily basis.

Applied learning-based color tone mapping for face recognition in video surveillance system

NASA Astrophysics Data System (ADS)

Yew, Chuu Tian; Suandi, Shahrel Azmin

2012-04-01

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Imaged Document Optical Correlation and Conversion System (IDOCCS)

NASA Astrophysics Data System (ADS)

Stalcup, Bruce W.; Dennis, Phillip W.; Dydyk, Robert B.

1999-03-01

Today, the paper document is fast becoming a thing of the past. With the rapid development of fast, inexpensive computing and storage devices, many government and private organizations are archiving their documents in electronic form (e.g., personnel records, medical records, patents, etc.). In addition, many organizations are converting their paper archives to electronic images, which are stored in a computer database. Because of this, there is a need to efficiently organize this data into comprehensive and accessible information resources. The Imaged Document Optical Correlation and Conversion System (IDOCCS) provides a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provides the search and retrieval capability of document images. The IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives and can even determine the types of languages contained within a document. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited, e.g., imaged documents containing an agency's seal or logo, or documents with a particular individual's signature block, can be singled out. With this dual capability, IDOCCS outperforms systems that rely on optical character recognition as a basis for indexing and storing only the textual content of documents for later retrieval.

VIEWCACHE: An incremental pointer-based access method for autonomous interoperable databases

NASA Technical Reports Server (NTRS)

Roussopoulos, N.; Sellis, Timos

1993-01-01

One of the biggest problems facing NASA today is to provide scientists efficient access to a large number of distributed databases. Our pointer-based incremental data base access method, VIEWCACHE, provides such an interface for accessing distributed datasets and directories. VIEWCACHE allows database browsing and search performing inter-database cross-referencing with no actual data movement between database sites. This organization and processing is especially suitable for managing Astrophysics databases which are physically distributed all over the world. Once the search is complete, the set of collected pointers pointing to the desired data are cached. VIEWCACHE includes spatial access methods for accessing image datasets, which provide much easier query formulation by referring directly to the image and very efficient search for objects contained within a two-dimensional window. We will develop and optimize a VIEWCACHE External Gateway Access to database management systems to facilitate database search.

On the Privacy Protection of Biometric Traits: Palmprint, Face, and Signature

NASA Astrophysics Data System (ADS)

Panigrahy, Saroj Kumar; Jena, Debasish; Korra, Sathya Babu; Jena, Sanjay Kumar

Biometrics are expected to add a new level of security to applications, as a person attempting access must prove who he or she really is by presenting a biometric to the system. The recent developments in the biometrics area have lead to smaller, faster and cheaper systems, which in turn has increased the number of possible application areas for biometric identity verification. The biometric data, being derived from human bodies (and especially when used to identify or verify those bodies) is considered personally identifiable information (PII). The collection, use and disclosure of biometric data — image or template, invokes rights on the part of an individual and obligations on the part of an organization. As biometric uses and databases grow, so do concerns that the personal data collected will not be used in reasonable and accountable ways. Privacy concerns arise when biometric data are used for secondary purposes, invoking function creep, data matching, aggregation, surveillance and profiling. Biometric data transmitted across networks and stored in various databases by others can also be stolen, copied, or otherwise misused in ways that can materially affect the individual involved. As Biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analysed before they are massively deployed in security systems. Along with security, also the privacy of the users is an important factor as the constructions of lines in palmprints contain personal characteristics, from face images a person can be recognised, and fake signatures can be practised by carefully watching the signature images available in the database. We propose a cryptographic approach to encrypt the images of palmprints, faces, and signatures by an advanced Hill cipher technique for hiding the information in the images. It also provides security to these images from being attacked by above mentioned attacks. So, during the feature extraction, the encrypted images are first decrypted, then the features are extracted, and used for identification or verification.

A multimedia comprehensive informatics system with decision support tools for a multi-site collaboration research of stroke rehabilitation

NASA Astrophysics Data System (ADS)

Wang, Ximing; Documet, Jorge; Garrison, Kathleen A.; Winstein, Carolee J.; Liu, Brent

2012-02-01

Stroke is a major cause of adult disability. The Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (I-CARE) clinical trial aims to evaluate a therapy for arm rehabilitation after stroke. A primary outcome measure is correlative analysis between stroke lesion characteristics and standard measures of rehabilitation progress, from data collected at seven research facilities across the country. Sharing and communication of brain imaging and behavioral data is thus a challenge for collaboration. A solution is proposed as a web-based system with tools supporting imaging and informatics related data. In this system, users may upload anonymized brain images through a secure internet connection and the system will sort the imaging data for storage in a centralized database. Users may utilize an annotation tool to mark up images. In addition to imaging informatics, electronic data forms, for example, clinical data forms, are also integrated. Clinical information is processed and stored in the database to enable future data mining related development. Tele-consultation is facilitated through the development of a thin-client image viewing application. For convenience, the system supports access through desktop PC, laptops, and iPAD. Thus, clinicians may enter data directly into the system via iPAD while working with participants in the study. Overall, this comprehensive imaging informatics system enables users to collect, organize and analyze stroke cases efficiently.

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.

Managing biomedical image metadata for search and retrieval of similar images.

PubMed

Korenblum, Daniel; Rubin, Daniel; Napel, Sandy; Rodriguez, Cesar; Beaulieu, Chris

2011-08-01

Radiology images are generally disconnected from the metadata describing their contents, such as imaging observations ("semantic" metadata), which are usually described in text reports that are not directly linked to the images. We developed a system, the Biomedical Image Metadata Manager (BIMM) to (1) address the problem of managing biomedical image metadata and (2) facilitate the retrieval of similar images using semantic feature metadata. Our approach allows radiologists, researchers, and students to take advantage of the vast and growing repositories of medical image data by explicitly linking images to their associated metadata in a relational database that is globally accessible through a Web application. BIMM receives input in the form of standard-based metadata files using Web service and parses and stores the metadata in a relational database allowing efficient data query and maintenance capabilities. Upon querying BIMM for images, 2D regions of interest (ROIs) stored as metadata are automatically rendered onto preview images included in search results. The system's "match observations" function retrieves images with similar ROIs based on specific semantic features describing imaging observation characteristics (IOCs). We demonstrate that the system, using IOCs alone, can accurately retrieve images with diagnoses matching the query images, and we evaluate its performance on a set of annotated liver lesion images. BIMM has several potential applications, e.g., computer-aided detection and diagnosis, content-based image retrieval, automating medical analysis protocols, and gathering population statistics like disease prevalences. The system provides a framework for decision support systems, potentially improving their diagnostic accuracy and selection of appropriate therapies.

Three-dimensional object recognition based on planar images

NASA Astrophysics Data System (ADS)

Mital, Dinesh P.; Teoh, Eam-Khwang; Au, K. C.; Chng, E. K.

1993-01-01

This paper presents the development and realization of a robotic vision system for the recognition of 3-dimensional (3-D) objects. The system can recognize a single object from among a group of known regular convex polyhedron objects that is constrained to lie on a calibrated flat platform. The approach adopted comprises a series of image processing operations on a single 2-dimensional (2-D) intensity image to derive an image line drawing. Subsequently, a feature matching technique is employed to determine 2-D spatial correspondences of the image line drawing with the model in the database. Besides its identification ability, the system can also provide important position and orientation information of the recognized object. The system was implemented on an IBM-PC AT machine executing at 8 MHz without the 80287 Maths Co-processor. In our overall performance evaluation based on a 600 recognition cycles test, the system demonstrated an accuracy of above 80% with recognition time well within 10 seconds. The recognition time is, however, indirectly dependent on the number of models in the database. The reliability of the system is also affected by illumination conditions which must be clinically controlled as in any industrial robotic vision system.

Imaged document information location and extraction using an optical correlator

NASA Astrophysics Data System (ADS)

Stalcup, Bruce W.; Dennis, Phillip W.; Dydyk, Robert B.

1999-12-01

Today, the paper document is fast becoming a thing of the past. With the rapid development of fast, inexpensive computing and storage devices, many government and private organizations are archiving their documents in electronic form (e.g., personnel records, medical records, patents, etc.). Many of these organizations are converting their paper archives to electronic images, which are then stored in a computer database. Because of this, there is a need to efficiently organize this data into comprehensive and accessible information resources and provide for rapid access to the information contained within these imaged documents. To meet this need, Litton PRC and Litton Data Systems Division are developing a system, the Imaged Document Optical Correlation and Conversion System (IDOCCS), to provide a total solution to the problem of managing and retrieving textual and graphic information from imaged document archives. At the heart of IDOCCS, optical correlation technology provide a means for the search and retrieval of information from imaged documents. IDOCCS can be used to rapidly search for key words or phrases within the imaged document archives and has the potential to determine the types of languages contained within a document. In addition, IDOCCS can automatically compare an input document with the archived database to determine if it is a duplicate, thereby reducing the overall resources required to maintain and access the document database. Embedded graphics on imaged pages can also be exploited, e.g., imaged documents containing an agency's seal or logo can be singled out. In this paper, we present a description of IDOCCS as well as preliminary performance results and theoretical projections.

An architecture for a brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.

2000-01-01

The widespread availability of methods for noninvasive assessment of brain structure has enabled researchers to investigate neuroimaging correlates of normal aging, cerebrovascular disease, and other processes; we designate such studies as image-based clinical trials (IBCTs). We propose an architecture for a brain-image database, which integrates image processing and statistical operators, and thus supports the implementation and analysis of IBCTs. The implementation of this architecture is described and results from the analysis of image and clinical data from two IBCTs are presented. We expect that systems such as this will play a central role in the management and analysis of complex research data sets.

Image BOSS: a biomedical object storage system

NASA Astrophysics Data System (ADS)

Stacy, Mahlon C.; Augustine, Kurt E.; Robb, Richard A.

1997-05-01

Researchers using biomedical images have data management needs which are oriented perpendicular to clinical PACS. The image BOSS system is designed to permit researchers to organize and select images based on research topic, image metadata, and a thumbnail of the image. Image information is captured from existing images in a Unix based filesystem, stored in an object oriented database, and presented to the user in a familiar laboratory notebook metaphor. In addition, the ImageBOSS is designed to provide an extensible infrastructure for future content-based queries directly on the images.

An ECG storage and retrieval system embedded in client server HIS utilizing object-oriented DB.

PubMed

Wang, C; Ohe, K; Sakurai, T; Nagase, T; Kaihara, S

1996-02-01

In the University of Tokyo Hospital, the improved client server HIS has been applied to clinical practice and physicians can order prescription, laboratory examination, ECG examination and radiographic examination, etc. directly by themselves and read results of these examinations, except medical signal waves, schema and image, on UNIX workstations. Recently, we designed and developed an ECG storage and retrieval system embedded in the client server HIS utilizing object-oriented database to take the first step in dealing with digitized signal, schema and image data and show waves, graphics, and images directly to physicians by the client server HIS. The system was developed based on object-oriented analysis and design, and implemented with object-oriented database management system (OODMS) and C++ programming language. In this paper, we describe the ECG data model, functions of the storage and retrieval system, features of user interface and the result of its implementation in the HIS.

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

PubMed

Zhang, Shaoting; Metaxas, Dimitris

2016-10-01

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

Morphology-based Query for Galaxy Image Databases

NASA Astrophysics Data System (ADS)

Shamir, Lior

2017-02-01

Galaxies of rare morphology are of paramount scientific interest, as they carry important information about the past, present, and future Universe. Once a rare galaxy is identified, studying it more effectively requires a set of galaxies of similar morphology, allowing generalization and statistical analysis that cannot be done when N=1. Databases generated by digital sky surveys can contain a very large number of galaxy images, and therefore once a rare galaxy of interest is identified it is possible that more instances of the same morphology are also present in the database. However, when a researcher identifies a certain galaxy of rare morphology in the database, it is virtually impossible to mine the database manually in the search for galaxies of similar morphology. Here we propose a computer method that can automatically search databases of galaxy images and identify galaxies that are morphologically similar to a certain user-defined query galaxy. That is, the researcher provides an image of a galaxy of interest, and the pattern recognition system automatically returns a list of galaxies that are visually similar to the target galaxy. The algorithm uses a comprehensive set of descriptors, allowing it to support different types of galaxies, and it is not limited to a finite set of known morphologies. While the list of returned galaxies is neither clean nor complete, it contains a far higher frequency of galaxies of the morphology of interest, providing a substantial reduction of the data. Such algorithms can be integrated into data management systems of autonomous digital sky surveys such as the Large Synoptic Survey Telescope (LSST), where the number of galaxies in the database is extremely large. The source code of the method is available at http://vfacstaff.ltu.edu/lshamir/downloads/udat.

The reference ballistic imaging database revisited.

PubMed

De Ceuster, Jan; Dujardin, Sylvain

2015-03-01

A reference ballistic image database (RBID) contains images of cartridge cases fired in firearms that are in circulation: a ballistic fingerprint database. The performance of an RBID was investigated a decade ago by De Kinder et al. using IBIS(®) Heritage™ technology. The results of that study were published in this journal, issue 214. Since then, technologies have evolved quite significantly and novel apparatus have become available on the market. The current research article investigates the efficiency of another automated ballistic imaging system, Evofinder(®) using the same database as used by De Kinder et al. The results demonstrate a significant increase in correlation efficiency: 38% of all matches were on first position of the Evofinder correlation list in comparison to IBIS(®) Heritage™ where only 19% were on the first position. Average correlation times are comparable to the IBIS(®) Heritage™ system. While Evofinder(®) demonstrates specific improvement for mutually correlating different ammunition brands, ammunition dependence of the markings is still strongly influencing the correlation result because the markings may vary considerably. As a consequence a great deal of potential hits (36%) was still far down in the correlation lists (positions 31 and lower). The large database was used to examine the probability of finding a match as a function of correlation list verification. As an example, the RBID study on Evofinder(®) demonstrates that to find at least 90% of all potential matches, at least 43% of the items in the database need to be compared on screen and this for breech face markings and firing pin impression separately. These results, although a clear improvement to the original RBID study, indicate that the implementation of such a database should still not be considered nowadays. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A smart technique for attendance system to recognize faces through parallelism

NASA Astrophysics Data System (ADS)

Prabhavathi, B.; Tanuja, V.; Madhu Viswanatham, V.; Rajashekhara Babu, M.

2017-11-01

Major part of recognising a person is face with the help of image processing techniques we can exploit the physical features of a person. In the old approach method that is used in schools and colleges it is there that the professor calls the student name and then the attendance for the students marked. Here in paper want to deviate from the old approach and go with the new approach by using techniques that are there in image processing. In this paper we presenting spontaneous presence for students in classroom. At first classroom image has been in use and after that image is kept in data record. For the images that are stored in the database we apply system algorithm which includes steps such as, histogram classification, noise removal, face detection and face recognition methods. So by using these steps we detect the faces and then compare it with the database. The attendance gets marked automatically if the system recognizes the faces.

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.

Scoring Package

National Institute of Standards and Technology Data Gateway

NIST Scoring Package (PC database for purchase)   The NIST Scoring Package (Special Database 1) is a reference implementation of the draft Standard Method for Evaluating the Performance of Systems Intended to Recognize Hand-printed Characters from Image Data Scanned from Forms.

Multimedia human brain database system for surgical candidacy determination in temporal lobe epilepsy with content-based image retrieval

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-01-01

This paper presents the development of a human brain multimedia database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted MRI and FLAIR MRI and ictal and interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication pretty much fits with the surgeons" expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Database for vertigo.

PubMed

Kentala, E; Pyykkö, I; Auramo, Y; Juhola, M

1995-03-01

An interactive database has been developed to assist the diagnostic procedure for vertigo and to store the data. The database offers a possibility to split and reunite the collected information when needed. It contains detailed information about a patient's history, symptoms, and findings in otoneurologic, audiologic, and imaging tests. The symptoms are classified into sets of questions on vertigo (including postural instability), hearing loss and tinnitus, and provoking factors. Confounding disorders are screened. The otoneurologic tests involve saccades, smooth pursuit, posturography, and a caloric test. In addition, findings from specific antibody tests, clinical neurotologic tests, magnetic resonance imaging, brain stem audiometry, and electrocochleography are included. The input information can be applied to workups for vertigo in an expert system called ONE. The database assists its user in that the input of information is easy. If not only can be used for diagnostic purposes but is also beneficial for research, and in combination with the expert system, it provides a tutorial guide for medical students.

Java-based PACS and reporting system for nuclear medicine

NASA Astrophysics Data System (ADS)

Slomka, Piotr J.; Elliott, Edward; Driedger, Albert A.

2000-05-01

In medical imaging practice, images and reports often need be reviewed and edited from many locations. We have designed and implemented a Java-based Remote Viewing and Reporting System (JaRRViS) for a nuclear medicine department, which is deployed as a web service, at the fraction of the cost dedicated PACS systems. The system can be extended to other imaging modalities. JaRRViS interfaces to the clinical patient databases of imaging workstations. Specialized nuclear medicine applets support interactive displays of data such as 3-D gated SPECT with all the necessary options such as cine, filtering, dynamic lookup tables, and reorientation. The reporting module is implemented as a separate applet using Java Foundation Classes (JFC) Swing Editor Kit and allows composition of multimedia reports after selection and annotation of appropriate images. The reports are stored on the server in the HTML format. JaRRViS uses Java Servlets for the preparation and storage of final reports. The http links to the reports or to the patient's raw images with applets can be obtained from JaRRViS by any Hospital Information System (HIS) via standard queries. Such links can be sent via e-mail or included as text fields in any HIS database, providing direct access to the patient reports and images via standard web browsers.

Case retrieval in medical databases by fusing heterogeneous information.

PubMed

Quellec, Gwénolé; Lamard, Mathieu; Cazuguel, Guy; Roux, Christian; Cochener, Béatrice

2011-01-01

A novel content-based heterogeneous information retrieval framework, particularly well suited to browse medical databases and support new generation computer aided diagnosis (CADx) systems, is presented in this paper. It was designed to retrieve possibly incomplete documents, consisting of several images and semantic information, from a database; more complex data types such as videos can also be included in the framework. The proposed retrieval method relies on image processing, in order to characterize each individual image in a document by their digital content, and information fusion. Once the available images in a query document are characterized, a degree of match, between the query document and each reference document stored in the database, is defined for each attribute (an image feature or a metadata). A Bayesian network is used to recover missing information if need be. Finally, two novel information fusion methods are proposed to combine these degrees of match, in order to rank the reference documents by decreasing relevance for the query. In the first method, the degrees of match are fused by the Bayesian network itself. In the second method, they are fused by the Dezert-Smarandache theory: the second approach lets us model our confidence in each source of information (i.e., each attribute) and take it into account in the fusion process for a better retrieval performance. The proposed methods were applied to two heterogeneous medical databases, a diabetic retinopathy database and a mammography screening database, for computer aided diagnosis. Precisions at five of 0.809 ± 0.158 and 0.821 ± 0.177, respectively, were obtained for these two databases, which is very promising.

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.

Web-based Hyper Suprime-Cam Data Providing System

NASA Astrophysics Data System (ADS)

Koike, M.; Furusawa, H.; Takata, T.; Price, P.; Okura, Y.; Yamada, Y.; Yamanoi, H.; Yasuda, N.; Bickerton, S.; Katayama, N.; Mineo, S.; Lupton, R.; Bosch, J.; Loomis, C.

2014-05-01

We describe a web-based user interface to retrieve Hyper Suprime-Cam data products, including images and. Users can access data directly from a graphical user interface or by writing a database SQL query. The system provides raw images, reduced images and stacked images (from multiple individual exposures), with previews available. Catalog queries can be executed in preview or queue mode, allowing for both exploratory and comprehensive investigations.

Content based information retrieval in forensic image databases.

PubMed

Geradts, Zeno; Bijhold, Jurrien

2002-03-01

This paper gives an overview of the various available image databases and ways of searching these databases on image contents. The developments in research groups of searching in image databases is evaluated and compared with the forensic databases that exist. Forensic image databases of fingerprints, faces, shoeprints, handwriting, cartridge cases, drugs tablets, and tool marks are described. The developments in these fields appear to be valuable for forensic databases, especially that of the framework in MPEG-7, where the searching in image databases is standardized. In the future, the combination of the databases (also DNA-databases) and possibilities to combine these can result in stronger forensic evidence.

[Design and development of an online system of parasite's images for training and evaluation].

PubMed

Yuan-Chun, Mao; Sui, Xu; Jie, Wang; Hua-Yun, Zhou; Jun, Cao

2017-08-08

To design and develop an online training and evaluation system for parasitic pathogen recognition. The system was based on a Parasitic Diseases Specimen Image Digitization Construction Database by using MYSQL 5.0 as the system of database development software, and PHP 5 as the interface development language. It was mainly used for online training and evaluation of parasitic pathology diagnostic techniques. The system interface was designed simple, flexible, and easy to operate for medical staff. It enabled full day and 24 hours accessible to online training study and evaluation. Thus, the system broke the time and space constraints of the traditional training models. The system provides a shared platform for the professional training of parasitic diseases, and a reference for other training tasks.

Toward More Accurate Iris Recognition Using Cross-Spectral Matching.

PubMed

Nalla, Pattabhi Ramaiah; Kumar, Ajay

2017-01-01

Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs, which continue to acquire millions of iris images to establish identity among billions. However, with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields model to significantly improve cross-domain iris recognition. The proposed domain adaptation framework based on the naive Bayes nearest neighbor classification uses a real-valued feature representation, which is capable of learning domain knowledge. Our approach to estimate corresponding visible iris patterns from the synthesis of iris patches in the near infrared iris images achieves outperforming results for the cross-spectral iris recognition. In this paper, a new class of bi-spectral iris recognition system that can simultaneously acquire visible and near infra-red images with pixel-to-pixel correspondences is proposed and evaluated. This paper presents experimental results from three publicly available databases; PolyU cross-spectral iris image database, IIITD CLI and UND database, and achieve outperforming results for the cross-sensor and cross-spectral iris matching.

The state of the art of medical imaging technology: from creation to archive and back.

PubMed

Gao, Xiaohong W; Qian, Yu; Hui, Rui

2011-01-01

Medical imaging has learnt itself well into modern medicine and revolutionized medical industry in the last 30 years. Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium. While this rich supply of images provides immeasurable information that would otherwise not be possible to obtain, medical images pose great challenges in archiving them safe from corrupted, lost and misuse, retrievable from databases of huge sizes with varying forms of metadata, and reusable when new tools for data mining and new media for data storing become available. This paper provides a summative account on the creation of medical imaging tomography, the development of image archiving systems and the innovation from the existing acquired image data pools. The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical images with variety of domains and different dimensions. In terms of novelties, the facilities of CBIR for 3D images coupled with image annotation in a fully automatic fashion have been developed and implemented in the system, resonating with future versatile, flexible and sustainable medical image databases that can reap new innovations.

The State of the Art of Medical Imaging Technology: from Creation to Archive and Back

PubMed Central

Gao, Xiaohong W; Qian, Yu; Hui, Rui

2011-01-01

Medical imaging has learnt itself well into modern medicine and revolutionized medical industry in the last 30 years. Stemming from the discovery of X-ray by Nobel laureate Wilhelm Roentgen, radiology was born, leading to the creation of large quantities of digital images as opposed to film-based medium. While this rich supply of images provides immeasurable information that would otherwise not be possible to obtain, medical images pose great challenges in archiving them safe from corrupted, lost and misuse, retrievable from databases of huge sizes with varying forms of metadata, and reusable when new tools for data mining and new media for data storing become available. This paper provides a summative account on the creation of medical imaging tomography, the development of image archiving systems and the innovation from the existing acquired image data pools. The focus of this paper is on content-based image retrieval (CBIR), in particular, for 3D images, which is exemplified by our developed online e-learning system, MIRAGE, home to a repository of medical images with variety of domains and different dimensions. In terms of novelties, the facilities of CBIR for 3D images coupled with image annotation in a fully automatic fashion have been developed and implemented in the system, resonating with future versatile, flexible and sustainable medical image databases that can reap new innovations. PMID:21915232

Needs assessment for next generation computer-aided mammography reference image databases and evaluation studies.

PubMed

Horsch, Alexander; Hapfelmeier, Alexander; Elter, Matthias

2011-11-01

Breast cancer is globally a major threat for women's health. Screening and adequate follow-up can significantly reduce the mortality from breast cancer. Human second reading of screening mammograms can increase breast cancer detection rates, whereas this has not been proven for current computer-aided detection systems as "second reader". Critical factors include the detection accuracy of the systems and the screening experience and training of the radiologist with the system. When assessing the performance of systems and system components, the choice of evaluation methods is particularly critical. Core assets herein are reference image databases and statistical methods. We have analyzed characteristics and usage of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM) from the University of South Florida, in literature indexed in Medline, IEEE Xplore, SpringerLink, and SPIE, with respect to type of computer-aided diagnosis (CAD) (detection, CADe, or diagnostics, CADx), selection of database subsets, choice of evaluation method, and quality of descriptions. 59 publications presenting 106 evaluation studies met our selection criteria. In 54 studies (50.9%), the selection of test items (cases, images, regions of interest) extracted from the DDSM was not reproducible. Only 2 CADx studies, not any CADe studies, used the entire DDSM. The number of test items varies from 100 to 6000. Different statistical evaluation methods are chosen. Most common are train/test (34.9% of the studies), leave-one-out (23.6%), and N-fold cross-validation (18.9%). Database-related terminology tends to be imprecise or ambiguous, especially regarding the term "case". Overall, both the use of the DDSM as data source for evaluation of mammography CAD systems, and the application of statistical evaluation methods were found highly diverse. Results reported from different studies are therefore hardly comparable. Drawbacks of the DDSM (e.g. varying quality of lesion annotations) may contribute to the reasons. But larger bias seems to be caused by authors' own decisions upon study design. RECOMMENDATIONS/CONCLUSION: For future evaluation studies, we derive a set of 13 recommendations concerning the construction and usage of a test database, as well as the application of statistical evaluation methods.

Accelerating Pathology Image Data Cross-Comparison on CPU-GPU Hybrid Systems

PubMed Central

Wang, Kaibo; Huai, Yin; Lee, Rubao; Wang, Fusheng; Zhang, Xiaodong; Saltz, Joel H.

2012-01-01

As an important application of spatial databases in pathology imaging analysis, cross-comparing the spatial boundaries of a huge amount of segmented micro-anatomic objects demands extremely data- and compute-intensive operations, requiring high throughput at an affordable cost. However, the performance of spatial database systems has not been satisfactory since their implementations of spatial operations cannot fully utilize the power of modern parallel hardware. In this paper, we provide a customized software solution that exploits GPUs and multi-core CPUs to accelerate spatial cross-comparison in a cost-effective way. Our solution consists of an efficient GPU algorithm and a pipelined system framework with task migration support. Extensive experiments with real-world data sets demonstrate the effectiveness of our solution, which improves the performance of spatial cross-comparison by over 18 times compared with a parallelized spatial database approach. PMID:23355955

Automatic detection of anomalies in screening mammograms

PubMed Central

2013-01-01

Background Diagnostic performance in breast screening programs may be influenced by the prior probability of disease. Since breast cancer incidence is roughly half a percent in the general population there is a large probability that the screening exam will be normal. That factor may contribute to false negatives. Screening programs typically exhibit about 83% sensitivity and 91% specificity. This investigation was undertaken to determine if a system could be developed to pre-sort screening-images into normal and suspicious bins based on their likelihood to contain disease. Wavelets were investigated as a method to parse the image data, potentially removing confounding information. The development of a classification system based on features extracted from wavelet transformed mammograms is reported. Methods In the multi-step procedure images were processed using 2D discrete wavelet transforms to create a set of maps at different size scales. Next, statistical features were computed from each map, and a subset of these features was the input for a concerted-effort set of naïve Bayesian classifiers. The classifier network was constructed to calculate the probability that the parent mammography image contained an abnormality. The abnormalities were not identified, nor were they regionalized. The algorithm was tested on two publicly available databases: the Digital Database for Screening Mammography (DDSM) and the Mammographic Images Analysis Society’s database (MIAS). These databases contain radiologist-verified images and feature common abnormalities including: spiculations, masses, geometric deformations and fibroid tissues. Results The classifier-network designs tested achieved sensitivities and specificities sufficient to be potentially useful in a clinical setting. This first series of tests identified networks with 100% sensitivity and up to 79% specificity for abnormalities. This performance significantly exceeds the mean sensitivity reported in literature for the unaided human expert. Conclusions Classifiers based on wavelet-derived features proved to be highly sensitive to a range of pathologies, as a result Type II errors were nearly eliminated. Pre-sorting the images changed the prior probability in the sorted database from 37% to 74%. PMID:24330643

Detailed description of the Mayo/IBM PACS

NASA Astrophysics Data System (ADS)

Gehring, Dale G.; Persons, Kenneth R.; Rothman, Melvyn L.; Salutz, James R.; Morin, Richard L.

1991-07-01

The Mayo Clinic and IBM/Rochester have jointly developed a picture archiving system (PACS) for use with Mayo's MRI and Neuro-CT imaging modalities. The system was developed to replace the imaging system's vendor-supplied magnetic tape archiving capability. The system consists of seven MR imagers and nine CT scanners, each interfaced to the PACS via IBM Personal System/2(tm) (PS/2) computers, which act as gateways from the imaging modality to the PACS network. The PAC system operates on the token-ring component of Mayo's city-wide local area network. Also on the PACS network are four optical storage subsystems used for image archival, three optical subsystems used for image retrieval, an IBM Application System/400(tm) (AS/400) computer used for database management and multiple PS/2-based image display systems and their image servers.

Global Picture Archiving and Communication Systems (GPACS): An Overview

DTIC Science & Technology

1994-04-01

a separate entity in most hospitals because of the integration problems that exilb. Eventually these systems should be connected so they appear to the...extremely important to efficient image data transfer include the protocol being used between the two transferring entities . Image data is currently...images, sound or video. The actual database consists of a collection of persistent data that is used by an application system of some entity , in this

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.

Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

2006-03-01

Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

Large image microscope array for the compilation of multimodality whole organ image databases.

PubMed

Namati, Eman; De Ryk, Jessica; Thiesse, Jacqueline; Towfic, Zaid; Hoffman, Eric; Mclennan, Geoffrey

2007-11-01

Three-dimensional, structural and functional digital image databases have many applications in education, research, and clinical medicine. However, to date, apart from cryosectioning, there have been no reliable means to obtain whole-organ, spatially conserving histology. Our aim was to generate a system capable of acquiring high-resolution images, featuring microscopic detail that could still be spatially correlated to the whole organ. To fulfill these objectives required the construction of a system physically capable of creating very fine whole-organ sections and collecting high-magnification and resolution digital images. We therefore designed a large image microscope array (LIMA) to serially section and image entire unembedded organs while maintaining the structural integrity of the tissue. The LIMA consists of several integrated components: a novel large-blade vibrating microtome, a 1.3 megapixel peltier cooled charge-coupled device camera, a high-magnification microscope, and a three axis gantry above the microtome. A custom control program was developed to automate the entire sectioning and automated raster-scan imaging sequence. The system is capable of sectioning unembedded soft tissue down to a thickness of 40 microm at specimen dimensions of 200 x 300 mm to a total depth of 350 mm. The LIMA system has been tested on fixed lung from sheep and mice, resulting in large high-quality image data sets, with minimal distinguishable disturbance in the delicate alveolar structures. Copyright 2007 Wiley-Liss, Inc.

Geometric database maintenance using CCTV cameras and overlay graphics

NASA Astrophysics Data System (ADS)

Oxenberg, Sheldon C.; Landell, B. Patrick; Kan, Edwin

1988-01-01

An interactive graphics system using closed circuit television (CCTV) cameras for remote verification and maintenance of a geometric world model database has been demonstrated in GE's telerobotics testbed. The database provides geometric models and locations of objects viewed by CCTV cameras and manipulated by telerobots. To update the database, an operator uses the interactive graphics system to superimpose a wireframe line drawing of an object with known dimensions on a live video scene containing that object. The methodology used is multipoint positioning to easily superimpose a wireframe graphic on the CCTV image of an object in the work scene. An enhanced version of GE's interactive graphics system will provide the object designation function for the operator control station of the Jet Propulsion Laboratory's telerobot demonstration system.

SenseLab

PubMed Central

Crasto, Chiquito J.; Marenco, Luis N.; Liu, Nian; Morse, Thomas M.; Cheung, Kei-Hoi; Lai, Peter C.; Bahl, Gautam; Masiar, Peter; Lam, Hugo Y.K.; Lim, Ernest; Chen, Huajin; Nadkarni, Prakash; Migliore, Michele; Miller, Perry L.; Shepherd, Gordon M.

2009-01-01

This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and BrainPharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab’s unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources. PMID:17510162

Design and evaluation of an imaging informatics system for analytics-based decision support in radiation therapy

NASA Astrophysics Data System (ADS)

Deshpande, Ruchi; DeMarco, John; Liu, Brent J.

2015-03-01

We have developed a comprehensive DICOM RT specific database of retrospective treatment planning data for radiation therapy of head and neck cancer. Further, we have designed and built an imaging informatics module that utilizes this database to perform data mining. The end-goal of this data mining system is to provide radiation therapy decision support for incoming head and neck cancer patients, by identifying best practices from previous patients who had the most similar tumor geometries. Since the performance of such systems often depends on the size and quality of the retrospective database, we have also placed an emphasis on developing infrastructure and strategies to encourage data sharing and participation from multiple institutions. The infrastructure and decision support algorithm have both been tested and evaluated with 51 sets of retrospective treatment planning data of head and neck cancer patients. We will present the overall design and architecture of our system, an overview of our decision support mechanism as well as the results of our evaluation.

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.

Mugshot Identification Database (MID)

National Institute of Standards and Technology Data Gateway

NIST Mugshot Identification Database (MID) (Web, free access)   NIST Special Database 18 is being distributed for use in development and testing of automated mugshot identification systems. The database consists of three CD-ROMs, containing a total of 3248 images of variable size using lossless compression. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

Medical image informatics infrastructure design and applications.

PubMed

Huang, H K; Wong, S T; Pietka, E

1997-01-01

Picture archiving and communication systems (PACS) is a system integration of multimodality images and health information systems designed for improving the operation of a radiology department. As it evolves, PACS becomes a hospital image document management system with a voluminous image and related data file repository. A medical image informatics infrastructure can be designed to take advantage of existing data, providing PACS with add-on value for health care service, research, and education. A medical image informatics infrastructure (MIII) consists of the following components: medical images and associated data (including PACS database), image processing, data/knowledge base management, visualization, graphic user interface, communication networking, and application oriented software. This paper describes these components and their logical connection, and illustrates some applications based on the concept of the MIII.

Building a medical image processing algorithm verification database

NASA Astrophysics Data System (ADS)

Brown, C. Wayne

2000-06-01

The design of a database containing head Computed Tomography (CT) studies is presented, along with a justification for the database's composition. The database will be used to validate software algorithms that screen normal head CT studies from studies that contain pathology. The database is designed to have the following major properties: (1) a size sufficient for statistical viability, (2) inclusion of both normal (no pathology) and abnormal scans, (3) inclusion of scans due to equipment malfunction, technologist error, and uncooperative patients, (4) inclusion of data sets from multiple scanner manufacturers, (5) inclusion of data sets from different gender and age groups, and (6) three independent diagnosis of each data set. Designed correctly, the database will provide a partial basis for FDA (United States Food and Drug Administration) approval of image processing algorithms for clinical use. Our goal for the database is the proof of viability of screening head CT's for normal anatomy using computer algorithms. To put this work into context, a classification scheme for 'computer aided diagnosis' systems is proposed.

An improved real time image detection system for elephant intrusion along the forest border areas.

PubMed

Sugumar, S J; Jayaparvathy, R

2014-01-01

Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

Development of a relational database to capture and merge clinical history with the quantitative results of radionuclide renography.

PubMed

Folks, Russell D; Savir-Baruch, Bital; Garcia, Ernest V; Verdes, Liudmila; Taylor, Andrew T

2012-12-01

Our objective was to design and implement a clinical history database capable of linking to our database of quantitative results from (99m)Tc-mercaptoacetyltriglycine (MAG3) renal scans and export a data summary for physicians or our software decision support system. For database development, we used a commercial program. Additional software was developed in Interactive Data Language. MAG3 studies were processed using an in-house enhancement of a commercial program. The relational database has 3 parts: a list of all renal scans (the RENAL database), a set of patients with quantitative processing results (the Q2 database), and a subset of patients from Q2 containing clinical data manually transcribed from the hospital information system (the CLINICAL database). To test interobserver variability, a second physician transcriber reviewed 50 randomly selected patients in the hospital information system and tabulated 2 clinical data items: hydronephrosis and presence of a current stent. The CLINICAL database was developed in stages and contains 342 fields comprising demographic information, clinical history, and findings from up to 11 radiologic procedures. A scripted algorithm is used to reliably match records present in both Q2 and CLINICAL. An Interactive Data Language program then combines data from the 2 databases into an XML (extensible markup language) file for use by the decision support system. A text file is constructed and saved for review by physicians. RENAL contains 2,222 records, Q2 contains 456 records, and CLINICAL contains 152 records. The interobserver variability testing found a 95% match between the 2 observers for presence or absence of ureteral stent (κ = 0.52), a 75% match for hydronephrosis based on narrative summaries of hospitalizations and clinical visits (κ = 0.41), and a 92% match for hydronephrosis based on the imaging report (κ = 0.84). We have developed a relational database system to integrate the quantitative results of MAG3 image processing with clinical records obtained from the hospital information system. We also have developed a methodology for formatting clinical history for review by physicians and export to a decision support system. We identified several pitfalls, including the fact that important textual information extracted from the hospital information system by knowledgeable transcribers can show substantial interobserver variation, particularly when record retrieval is based on the narrative clinical records.

Digital Image Support in the ROADNet Real-time Monitoring Platform

NASA Astrophysics Data System (ADS)

Lindquist, K. G.; Hansen, T. S.; Newman, R. L.; Vernon, F. L.; Nayak, A.; Foley, S.; Fricke, T.; Orcutt, J.; Rajasekar, A.

2004-12-01

The ROADNet real-time monitoring infrastructure has allowed researchers to integrate geophysical monitoring data from a wide variety of signal domains. Antelope-based data transport, relational-database buffering and archiving, backup/replication/archiving through the Storage Resource Broker, and a variety of web-based distribution tools create a powerful monitoring platform. In this work we discuss our use of the ROADNet system for the collection and processing of digital image data. Remote cameras have been deployed at approximately 32 locations as of September 2004, including the SDSU Santa Margarita Ecological Reserve, the Imperial Beach pier, and the Pinon Flats geophysical observatory. Fire monitoring imagery has been obtained through a connection to the HPWREN project. Near-real-time images obtained from the R/V Roger Revelle include records of seafloor operations by the JASON submersible, as part of a maintenance mission for the H2O underwater seismic observatory. We discuss acquisition mechanisms and the packet architecture for image transport via Antelope orbservers, including multi-packet support for arbitrarily large images. Relational database storage supports archiving of timestamped images, image-processing operations, grouping of related images and cameras, support for motion-detect triggers, thumbnail images, pre-computed video frames, support for time-lapse movie generation and storage of time-lapse movies. Available ROADNet monitoring tools include both orbserver-based display of incoming real-time images and web-accessible searching and distribution of images and movies driven by the relational database (http://mercali.ucsd.edu/rtapps/rtimbank.php). An extension to the Kepler Scientific Workflow System also allows real-time image display via the Ptolemy project. Custom time-lapse movies may be made from the ROADNet web pages.

Multigeneration data migration from legacy systems

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Liu, Brent J.; Kho, Hwa T.; Tao, Wenchao; Wang, Cun; McCoy, J. Michael

2003-05-01

The migration of image data from different generations of legacy archive systems represents a technical challenge and in incremental cost in transitions to newer generations of PACS. UCLA medical center has elected to completely replace the existing PACS infrastructure encompassing several generations of legacy systems by a new commercial system providing enterprise-wide image management and communication. One of the most challenging parts of the project was the migration of large volumes of legacy images into the new system. Planning of the migration required the development of specialized software and hardware, and included different phases of data mediation from existing databases to the new PACS database prior to the migration of the image data. The project plan included a detailed analysis of resources and cost of data migration to optimize the process and minimize the delay of a hybrid operation where the legacy systems need to remain operational. Our analysis and project planning showed that the data migration represents the most critical path in the process of PACS renewal. Careful planning and optimization of the project timeline and resources allocated is critical to minimize the financial impact and the time delays that such migrations can impose on the implementation plan.

Psychophysical studies of the performance of an image database retrieval system

NASA Astrophysics Data System (ADS)

Papathomas, Thomas V.; Conway, Tiffany E.; Cox, Ingemar J.; Ghosn, Joumana; Miller, Matt L.; Minka, Thomas P.; Yianilos, Peter N.

1998-07-01

We describe psychophysical experiments conducted to study PicHunter, a content-based image retrieval (CBIR) system. Experiment 1 studies the importance of using (a) semantic information, (2) memory of earlier input and (3) relative, rather than absolute, judgements of image similarity. The target testing paradigm is used in which a user must search for an image identical to a target. We find that the best performance comes from a version of PicHunter that uses only semantic cues, with memory and relative similarity judgements. Second best is use of both pictorial and semantic cues, with memory and relative similarity judgements. Most reports of CBIR systems provide only qualitative measures of performance based on how similar retrieved images are to a target. Experiment 2 puts PicHunter into this context with a more rigorous test. We first establish a baseline for our database by measuring the time required to find an image that is similar to a target when the images are presented in random order. Although PicHunter's performance is measurably better than this, the test is weak because even random presentation of images yields reasonably short search times. This casts doubt on the strength of results given in other reports where no baseline is established.

3D THz hyperspectrum applied in security check-in

NASA Astrophysics Data System (ADS)

Damian, V.; Logofǎtu, P. C.; Vasile, T.

2016-12-01

We developed a measuring technology using a TDS-THz system to construct hyperspectral images of some objects, including hazardous materials. "T-rays" (the THz spectral domain of the light) have a growing importance in security and imagistic domain. Due to their property of penetrating through dielectric objects, and using non-ionizing radiations, the THz systems have become a standard for "hot-places" (airports, train stations etc.). The hyperspectral images are 3D images having 2D spatial dimension and one spectral dimension. In this way, we obtain simultaneously information about the form of the object and its molecular composition. For discriminating between substances, we must first build a database of spectra for hazardous and dangerous substances. We experiment our system on some items (among them a firecracker, a cigarette and a metal collar) and we tried to discriminate between them using the database of spectra.

Dual Resolution Images from Paired Fingerprint Cards

National Institute of Standards and Technology Data Gateway

NIST Dual Resolution Images from Paired Fingerprint Cards (Web, free access)   NIST Special Database 30 is being distributed for use in development and testing of fingerprint compression and fingerprint matching systems. The database allows the user to develop and evaluate data compression algorithms for fingerprint images scanned at both 19.7 ppmm (500 dpi) and 39.4 ppmm (1000 dpi). The data consist of 36 ten-print paired cards with both the rolled and plain images scanned at 19.7 and 39.4 pixels per mm. A newer version of the compression/decompression software on the CDROM can be found at the website http://www.nist.gov/itl/iad/ig/nigos.cfm as part of the NBIS package.

DICOM-compliant PACS with CD-based image archival

NASA Astrophysics Data System (ADS)

Cox, Robert D.; Henri, Christopher J.; Rubin, Richard K.; Bret, Patrice M.

1998-07-01

This paper describes the design and implementation of a low- cost PACS conforming to the DICOM 3.0 standard. The goal was to provide an efficient image archival and management solution on a heterogeneous hospital network as a basis for filmless radiology. The system follows a distributed, client/server model and was implemented at a fraction of the cost of a commercial PACS. It provides reliable archiving on recordable CD and allows access to digital images throughout the hospital and on the Internet. Dedicated servers have been designed for short-term storage, CD-based archival, data retrieval and remote data access or teleradiology. The short-term storage devices provide DICOM storage and query/retrieve services to scanners and workstations and approximately twelve weeks of 'on-line' image data. The CD-based archival and data retrieval processes are fully automated with the exception of CD loading and unloading. The system employs lossless compression on both short- and long-term storage devices. All servers communicate via the DICOM protocol in conjunction with both local and 'master' SQL-patient databases. Records are transferred from the local to the master database independently, ensuring that storage devices will still function if the master database server cannot be reached. The system features rules-based work-flow management and WWW servers to provide multi-platform remote data access. The WWW server system is distributed on the storage, retrieval and teleradiology servers allowing viewing of locally stored image data directly in a WWW browser without the need for data transfer to a central WWW server. An independent system monitors disk usage, processes, network and CPU load on each server and reports errors to the image management team via email. The PACS was implemented using a combination of off-the-shelf hardware, freely available software and applications developed in-house. The system has enabled filmless operation in CT, MR and ultrasound within the radiology department and throughout the hospital. The use of WWW technology has enabled the development of an intuitive we- based teleradiology and image management solution that provides complete access to image data.

Realizing parameterless automatic classification of remote sensing imagery using ontology engineering and cyberinfrastructure techniques

NASA Astrophysics Data System (ADS)

Sun, Ziheng; Fang, Hui; Di, Liping; Yue, Peng

2016-09-01

It was an untouchable dream for remote sensing experts to realize total automatic image classification without inputting any parameter values. Experts usually spend hours and hours on tuning the input parameters of classification algorithms in order to obtain the best results. With the rapid development of knowledge engineering and cyberinfrastructure, a lot of data processing and knowledge reasoning capabilities become online accessible, shareable and interoperable. Based on these recent improvements, this paper presents an idea of parameterless automatic classification which only requires an image and automatically outputs a labeled vector. No parameters and operations are needed from endpoint consumers. An approach is proposed to realize the idea. It adopts an ontology database to store the experiences of tuning values for classifiers. A sample database is used to record training samples of image segments. Geoprocessing Web services are used as functionality blocks to finish basic classification steps. Workflow technology is involved to turn the overall image classification into a total automatic process. A Web-based prototypical system named PACS (Parameterless Automatic Classification System) is implemented. A number of images are fed into the system for evaluation purposes. The results show that the approach could automatically classify remote sensing images and have a fairly good average accuracy. It is indicated that the classified results will be more accurate if the two databases have higher quality. Once the experiences and samples in the databases are accumulated as many as an expert has, the approach should be able to get the results with similar quality to that a human expert can get. Since the approach is total automatic and parameterless, it can not only relieve remote sensing workers from the heavy and time-consuming parameter tuning work, but also significantly shorten the waiting time for consumers and facilitate them to engage in image classification activities. Currently, the approach is used only on high resolution optical three-band remote sensing imagery. The feasibility using the approach on other kinds of remote sensing images or involving additional bands in classification will be studied in future.

Role of HIS/RIS DICOM interfaces in the integration of imaging into the Department of Veterans Affairs healthcare enterprise

NASA Astrophysics Data System (ADS)

Kuzmak, Peter M.; Dayhoff, Ruth E.

1998-07-01

The U.S. Department of Veterans Affairs is integrating imaging into the healthcare enterprise using the Digital Imaging and Communication in Medicine (DICOM) standard protocols. Image management is directly integrated into the VistA Hospital Information System (HIS) software and clinical database. Radiology images are acquired via DICOM, and are stored directly in the HIS database. Images can be displayed on low- cost clinician's workstations throughout the medical center. High-resolution diagnostic quality multi-monitor VistA workstations with specialized viewing software can be used for reading radiology images. DICOM has played critical roles in the ability to integrate imaging functionality into the Healthcare Enterprise. Because of its openness, it allows the integration of system components from commercial and non- commercial sources to work together to provide functional cost-effective solutions (see Figure 1). Two approaches are used to acquire and handle images within the radiology department. At some VA Medical Centers, DICOM is used to interface a commercial Picture Archiving and Communications System (PACS) to the VistA HIS. At other medical centers, DICOM is used to interface the image producing modalities directly to the image acquisition and display capabilities of VistA itself. Both of these approaches use a small set of DICOM services that has been implemented by VistA to allow patient and study text data to be transmitted to image producing modalities and the commercial PACS, and to enable images and study data to be transferred back.

[A computer-aided image diagnosis and study system].

PubMed

Li, Zhangyong; Xie, Zhengxiang

2004-08-01

The revolution in information processing, particularly the digitizing of medicine, has changed the medical study, work and management. This paper reports a method to design a system for computer-aided image diagnosis and study. Combined with some good idea of graph-text system and picture archives communicate system (PACS), the system was realized and used for "prescription through computer", "managing images" and "reading images under computer and helping the diagnosis". Also typical examples were constructed in a database and used to teach the beginners. The system was developed by the visual developing tools based on object oriented programming (OOP) and was carried into operation on the Windows 9X platform. The system possesses friendly man-machine interface.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

Information-theoretic CAD system in mammography: Entropy-based indexing for computational efficiency and robust performance

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

Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee

2007-08-15

We have previously presented a knowledge-based computer-assisted detection (KB-CADe) system for the detection of mammographic masses. The system is designed to compare a query mammographic region with mammographic templates of known ground truth. The templates are stored in an adaptive knowledge database. Image similarity is assessed with information theoretic measures (e.g., mutual information) derived directly from the image histograms. A previous study suggested that the diagnostic performance of the system steadily improves as the knowledge database is initially enriched with more templates. However, as the database increases in size, an exhaustive comparison of the query case with each stored templatemore » becomes computationally burdensome. Furthermore, blind storing of new templates may result in redundancies that do not necessarily improve diagnostic performance. To address these concerns we investigated an entropy-based indexing scheme for improving the speed of analysis and for satisfying database storage restrictions without compromising the overall diagnostic performance of our KB-CADe system. The indexing scheme was evaluated on two different datasets as (i) a search mechanism to sort through the knowledge database, and (ii) a selection mechanism to build a smaller, concise knowledge database that is easier to maintain but still effective. There were two important findings in the study. First, entropy-based indexing is an effective strategy to identify fast a subset of templates that are most relevant to a given query. Only this subset could be analyzed in more detail using mutual information for optimized decision making regarding the query. Second, a selective entropy-based deposit strategy may be preferable where only high entropy cases are maintained in the knowledge database. Overall, the proposed entropy-based indexing scheme was shown to reduce the computational cost of our KB-CADe system by 55% to 80% while maintaining the system's diagnostic performance.« less

Analysis and Exchange of Multimedia Laboratory Data Using the Brain Database

PubMed Central

Wertheim, Steven L.

1990-01-01

Two principal goals of the Brain Database are: 1) to support laboratory data collection and analysis of multimedia information about the nervous system and 2) to support exchange of these data among researchers and clinicians who may be physically distant. This has been achieved by an implementation of experimental and clinical records within a relational database. An Image Series Editor has been created that provides a graphical interface to these data for the purposes of annotation, quantification and other analyses. Cooperating laboratories each maintain their own copies of the Brain Database to which they may add private data. Although the data in a given experimental or patient record will be distributed among many tables and external image files, the user can treat each record as a unit that can be extracted from the local database and sent to a distant colleague.

PhamDB: a web-based application for building Phamerator databases.

PubMed

Lamine, James G; DeJong, Randall J; Nelesen, Serita M

2016-07-01

PhamDB is a web application which creates databases of bacteriophage genes, grouped by gene similarity. It is backwards compatible with the existing Phamerator desktop software while providing an improved database creation workflow. Key features include a graphical user interface, validation of uploaded GenBank files, and abilities to import phages from existing databases, modify existing databases and queue multiple jobs. Source code and installation instructions for Linux, Windows and Mac OSX are freely available at https://github.com/jglamine/phage PhamDB is also distributed as a docker image which can be managed via Kitematic. This docker image contains the application and all third party software dependencies as a pre-configured system, and is freely available via the installation instructions provided. snelesen@calvin.edu. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Collection Fusion Using Bayesian Estimation of a Linear Regression Model in Image Databases on the Web.

ERIC Educational Resources Information Center

Kim, Deok-Hwan; Chung, Chin-Wan

2003-01-01

Discusses the collection fusion problem of image databases, concerned with retrieving relevant images by content based retrieval from image databases distributed on the Web. Focuses on a metaserver which selects image databases supporting similarity measures and proposes a new algorithm which exploits a probabilistic technique using Bayesian…

Development of a mobile emergency patient information and imaging communication system based on CDMA-1X EVDO

NASA Astrophysics Data System (ADS)

Yang, Keon Ho; Jung, Haijo; Kang, Won-Suk; Jang, Bong Mun; Kim, Joong Il; Han, Dong Hoon; Yoo, Sun-Kook; Yoo, Hyung-Sik; Kim, Hee-Joung

2006-03-01

The wireless mobile service with a high bit rate using CDMA-1X EVDO is now widely used in Korea. Mobile devices are also increasingly being used as the conventional communication mechanism. We have developed a web-based mobile system that communicates patient information and images, using CDMA-1X EVDO for emergency diagnosis. It is composed of a Mobile web application system using the Microsoft Windows 2003 server and an internet information service. Also, a mobile web PACS used for a database managing patient information and images was developed by using Microsoft access 2003. A wireless mobile emergency patient information and imaging communication system is developed by using Microsoft Visual Studio.NET, and JPEG 2000 ActiveX control for PDA phone was developed by using the Microsoft Embedded Visual C++. Also, the CDMA-1X EVDO is used for connections between mobile web servers and the PDA phone. This system allows fast access to the patient information database, storing both medical images and patient information anytime and anywhere. Especially, images were compressed into a JPEG2000 format and transmitted from a mobile web PACS inside the hospital to the radiologist using a PDA phone located outside the hospital. Also, this system shows radiological images as well as physiological signal data, including blood pressure, vital signs and so on, in the web browser of the PDA phone so radiologists can diagnose more effectively. Also, we acquired good results using an RW-6100 PDA phone used in the university hospital system of the Sinchon Severance Hospital in Korea.

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

Reconfigurable Image Generator

NASA Technical Reports Server (NTRS)

Archdeacon, John L. (Inventor); Iwai, Nelson H. (Inventor); Kato, Kenji H. (Inventor); Sweet, Barbara T. (Inventor)

2017-01-01

A RiG may simulate visual conditions of a real world environment, and generate the necessary amount of pixels in a visual simulation at rates up to 120 frames per second. RiG may also include a database generation system capable of producing visual databases suitable to drive the visual fidelity required by the RiG.

Vanderbilt University Institute of Imaging Science Center for Computational Imaging XNAT: A multimodal data archive and processing environment.

PubMed

Harrigan, Robert L; Yvernault, Benjamin C; Boyd, Brian D; Damon, Stephen M; Gibney, Kyla David; Conrad, Benjamin N; Phillips, Nicholas S; Rogers, Baxter P; Gao, Yurui; Landman, Bennett A

2016-01-01

The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has developed a database built on XNAT housing over a quarter of a million scans. The database provides framework for (1) rapid prototyping, (2) large scale batch processing of images and (3) scalable project management. The system uses the web-based interfaces of XNAT and REDCap to allow for graphical interaction. A python middleware layer, the Distributed Automation for XNAT (DAX) package, distributes computation across the Vanderbilt Advanced Computing Center for Research and Education high performance computing center. All software are made available in open source for use in combining portable batch scripting (PBS) grids and XNAT servers. Copyright © 2015 Elsevier Inc. All rights reserved.

A novel image database analysis system maintenance of transportation facility.

DOT National Transportation Integrated Search

2009-01-01

The current project was funded by MIOH-UTC in the Spring of 2008 to investigate efficient : maintenance methods for transportation facilities. To achieve the objectives of the project, the : PIs undertook the research of various technologies of image...

High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

2005-09-01

Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

[Mobile phone-computer wireless interactive graphics transmission technology and its medical application].

PubMed

Huang, Shuo; Liu, Jing

2010-05-01

Application of clinical digital medical imaging has raised many tough issues to tackle, such as data storage, management, and information sharing. Here we investigated a mobile phone based medical image management system which is capable of achieving personal medical imaging information storage, management and comprehensive health information analysis. The technologies related to the management system spanning the wireless transmission technology, the technical capabilities of phone in mobile health care and management of mobile medical database were discussed. Taking medical infrared images transmission between phone and computer as an example, the working principle of the present system was demonstrated.

Teaching resources for dermatology on the WWW--quiz system and dynamic lecture scripts using a HTTP-database demon.

PubMed Central

Bittorf, A.; Diepgen, T. L.

1996-01-01

The World Wide Web (WWW) is becoming the major way of acquiring information in all scientific disciplines as well as in business. It is very well suitable for fast distribution and exchange of up to date teaching resources. However, to date most teaching applications on the Web do not use its full power by integrating interactive components. We have set up a computer based training (CBT) framework for Dermatology, which consists of dynamic lecture scripts, case reports, an atlas and a quiz system. All these components heavily rely on an underlying image database that permits the creation of dynamic documents. We used a demon process that keeps the database open and can be accessed using HTTP to achieve better performance and avoid the overhead involved by starting CGI-processes. The result of our evaluation was very encouraging. Images Figure 3 PMID:8947625

RTS2: a powerful robotic observatory manager

NASA Astrophysics Data System (ADS)

Kubánek, Petr; Jelínek, Martin; Vítek, Stanislav; de Ugarte Postigo, Antonio; Nekola, Martin; French, John

2006-06-01

RTS2, or Remote Telescope System, 2nd Version, is an integrated package for remote telescope control under the Linux operating system. It is designed to run in fully autonomous mode, picking targets from a database table, storing image meta data to the database, processing images and storing their WCS coordinates in the database and offering Virtual-Observatory enabled access to them. It is currently running on various telescope setups world-wide. For control of devices from various manufacturers we developed an abstract device layer, enabling control of all possible combinations of mounts, CCDs, photometers, roof and cupola controllers. We describe the evolution of RTS2 from Python-based RTS to C and later C++ based RTS2, focusing on the problems we faced during development. The internal structure of RTS2, focusing on object layering, which is used to uniformly control various devices and provides uniform reporting layer, is also discussed.

Utilisation of a thoracic oncology database to capture radiological and pathological images for evaluation of response to chemotherapy in patients with malignant pleural mesothelioma

PubMed Central

Carey, George B; Kazantsev, Stephanie; Surati, Mosmi; Rolle, Cleo E; Kanteti, Archana; Sadiq, Ahad; Bahroos, Neil; Raumann, Brigitte; Madduri, Ravi; Dave, Paul; Starkey, Adam; Hensing, Thomas; Husain, Aliya N; Vokes, Everett E; Vigneswaran, Wickii; Armato, Samuel G; Kindler, Hedy L; Salgia, Ravi

2012-01-01

Objective An area of need in cancer informatics is the ability to store images in a comprehensive database as part of translational cancer research. To meet this need, we have implemented a novel tandem database infrastructure that facilitates image storage and utilisation. Background We had previously implemented the Thoracic Oncology Program Database Project (TOPDP) database for our translational cancer research needs. While useful for many research endeavours, it is unable to store images, hence our need to implement an imaging database which could communicate easily with the TOPDP database. Methods The Thoracic Oncology Research Program (TORP) imaging database was designed using the Research Electronic Data Capture (REDCap) platform, which was developed by Vanderbilt University. To demonstrate proof of principle and evaluate utility, we performed a retrospective investigation into tumour response for malignant pleural mesothelioma (MPM) patients treated at the University of Chicago Medical Center with either of two analogous chemotherapy regimens and consented to at least one of two UCMC IRB protocols, 9571 and 13473A. Results A cohort of 22 MPM patients was identified using clinical data in the TOPDP database. After measurements were acquired, two representative CT images and 0–35 histological images per patient were successfully stored in the TORP database, along with clinical and demographic data. Discussion We implemented the TORP imaging database to be used in conjunction with our comprehensive TOPDP database. While it requires an additional effort to use two databases, our database infrastructure facilitates more comprehensive translational research. Conclusions The investigation described herein demonstrates the successful implementation of this novel tandem imaging database infrastructure, as well as the potential utility of investigations enabled by it. The data model presented here can be utilised as the basis for further development of other larger, more streamlined databases in the future. PMID:23103606

Image-based diagnostic aid for interstitial lung disease with secondary data integration

NASA Astrophysics Data System (ADS)

Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine

2007-03-01

Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns. These features show good discriminative properties for the separation of five classes of visual observations.

Designing for Peta-Scale in the LSST Database

NASA Astrophysics Data System (ADS)

Kantor, J.; Axelrod, T.; Becla, J.; Cook, K.; Nikolaev, S.; Gray, J.; Plante, R.; Nieto-Santisteban, M.; Szalay, A.; Thakar, A.

2007-10-01

The Large Synoptic Survey Telescope (LSST), a proposed ground-based 8.4 m telescope with a 10 deg^2 field of view, will generate 15 TB of raw images every observing night. When calibration and processed data are added, the image archive, catalogs, and meta-data will grow 15 PB yr^{-1} on average. The LSST Data Management System (DMS) must capture, process, store, index, replicate, and provide open access to this data. Alerts must be triggered within 30 s of data acquisition. To do this in real-time at these data volumes will require advances in data management, database, and file system techniques. This paper describes the design of the LSST DMS and emphasizes features for peta-scale data. The LSST DMS will employ a combination of distributed database and file systems, with schema, partitioning, and indexing oriented for parallel operations. Image files are stored in a distributed file system with references to, and meta-data from, each file stored in the databases. The schema design supports pipeline processing, rapid ingest, and efficient query. Vertical partitioning reduces disk input/output requirements, horizontal partitioning allows parallel data access using arrays of servers and disks. Indexing is extensive, utilizing both conventional RAM-resident indexes and column-narrow, row-deep tag tables/covering indices that are extracted from tables that contain many more attributes. The DMS Data Access Framework is encapsulated in a middleware framework to provide a uniform service interface to all framework capabilities. This framework will provide the automated work-flow, replication, and data analysis capabilities necessary to make data processing and data quality analysis feasible at this scale.

Comparative Study Of Image Enhancement Algorithms For Digital And Film Mammography

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

Delgado-Gonzalez, A.; Sanmiguel, R. E.

2008-08-11

Here we discuss the application of edge enhancement algorithms on images obtained with a Mammography System which has a Selenium Detector and on the other hand, on images obtained from digitized film mammography. Comparative analysis of such images includes the study of technical aspects of image acquisition, storage, compression and display. A protocol for a local database has been created as a result of this study.

Combined semantic and similarity search in medical image databases

NASA Astrophysics Data System (ADS)

Seifert, Sascha; Thoma, Marisa; Stegmaier, Florian; Hammon, Matthias; Kramer, Martin; Huber, Martin; Kriegel, Hans-Peter; Cavallaro, Alexander; Comaniciu, Dorin

2011-03-01

The current diagnostic process at hospitals is mainly based on reviewing and comparing images coming from multiple time points and modalities in order to monitor disease progression over a period of time. However, for ambiguous cases the radiologist deeply relies on reference literature or second opinion. Although there is a vast amount of acquired images stored in PACS systems which could be reused for decision support, these data sets suffer from weak search capabilities. Thus, we present a search methodology which enables the physician to fulfill intelligent search scenarios on medical image databases combining ontology-based semantic and appearance-based similarity search. It enabled the elimination of 12% of the top ten hits which would arise without taking the semantic context into account.

Virtual setting for training in interpreting mammography images

NASA Astrophysics Data System (ADS)

Pezzuol, J. L.; Abreu, F. D. L.; Silva, S. M.; Tendolini, A.; Bissaco, M. A. Se; Rodrigues, S. C. M.

2017-03-01

This work presents a web system for the training of students or residents (users) interested in the detection of breast density in mammography images. The system consists of a breast imaging database with breast density types classified and demarcated by the specialist (tutor) or online database. The planning was based on ISO / IEC 12207. Through the browser (desktop or notebook), the user will visualize the breast images and in them will realize the markings of the density region and even classify them per the BI-RADS protocol. After marking, this will be compared to the gold standard already existing in the image base, and then the system will inform if the area demarcation has been set or not. The shape of this marking is similar to the paint brush. The evaluation was based on ISO / IEC 1926 or 25010: 2011 by 3 software development specialists and 3 in mammary radiology, evaluating usability, configuration, performance and System interface through the Likert scale-based questionnaire. Where they have totally agreed on usability, configuration, performance and partially on the interface. And as a good thing: the system is able to be accessed anywhere and at any time, the hit or error response is in real time, it can be used in the educational area, the limit of the amount of images will depend on the size of the computer memory, At the end the system sends the results achieved by e-mail to the user, reproduction of the system on any type of screen, complementation of the system with other types of breast structures. Negative points are the need for internet.

Puncture-proof picture archiving and communication system.

PubMed

Willis, C E; McCluggage, C W; Orand, M R; Parker, B R

2001-06-01

As we become increasingly dependent on our picture archiving and communications system (PACS) for the clinical practice of medicine, the demand for improved reliability becomes urgent. Borrowing principles from the discipline of Reliability Engineering, we have identified components of our system that constitute single points of failure and have endeavored to eliminate these through redundant components and manual work-around procedures. To assess the adequacy of our preparations, we have identified a set of plausible events that could interfere with the function of one or more of our PACS components. These events could be as simple as the loss of the network connection to a single component or as broad as the loss of our central data center. We have identified the need to continue to operate during adverse conditions, as well as the requirement to recover rapidly from major disruptions in service. This assessment led us to modify the physical locations of central PACS components within our physical plant. We are also taking advantage of actual disruptive events coincident with a major expansion of our facility to test our recovery procedures. Based on our recognition of the vital nature of our electronic images for patient care, we are now recording electronic images in two copies on disparate media. The image database is critical to both continued operations and recovery. Restoration of the database from periodic tape backups with a 24-hour cycle time may not support our clinical scenario: acquisition modalities have a limited local storage capacity, some of which will not contain the daily workload. Restoration of the database from the archived media is an exceedingly slow process, that will likely not meet our requirement to restore clinical operations without significant delay. Our PACS vendor is working on concurrent image databases that would be capable of nearly immediate switchover and recovery.

Neural networks for computer-aided diagnosis: detection of lung nodules in chest radiograms.

PubMed

Coppini, Giuseppe; Diciotti, Stefano; Falchini, Massimo; Villari, Natale; Valli, Guido

2003-12-01

The paper describes a neural-network-based system for the computer aided detection of lung nodules in chest radiograms. Our approach is based on multiscale processing and artificial neural networks (ANNs). The problem of nodule detection is faced by using a two-stage architecture including: 1) an attention focusing subsystem that processes whole radiographs to locate possible nodular regions ensuring high sensitivity; 2) a validation subsystem that processes regions of interest to evaluate the likelihood of the presence of a nodule, so as to reduce false alarms and increase detection specificity. Biologically inspired filters (both LoG and Gabor kernels) are used to enhance salient image features. ANNs of the feedforward type are employed, which allow an efficient use of a priori knowledge about the shape of nodules, and the background structure. The images from the public JSRT database, including 247 radiograms, were used to build and test the system. We performed a further test by using a second private database with 65 radiograms collected and annotated at the Radiology Department of the University of Florence. Both data sets include nodule and nonnodule radiographs. The use of a public data set along with independent testing with a different image set makes the comparison with other systems easier and allows a deeper understanding of system behavior. Experimental results are described by ROC/FROC analysis. For the JSRT database, we observed that by varying sensitivity from 60 to 75% the number of false alarms per image lies in the range 4-10, while accuracy is in the range 95.7-98.0%. When the second data set was used comparable results were obtained. The observed system performances support the undertaking of system validation in clinical settings.

Assuring image authenticity within a data grid using lossless digital signature embedding and a HIPAA-compliant auditing system

NASA Astrophysics Data System (ADS)

Lee, Jasper C.; Ma, Kevin C.; Liu, Brent J.

2008-03-01

A Data Grid for medical images has been developed at the Image Processing and Informatics Laboratory, USC to provide distribution and fault-tolerant storage of medical imaging studies across Internet2 and public domain. Although back-up policies and grid certificates guarantee privacy and authenticity of grid-access-points, there still lacks a method to guarantee the sensitive DICOM images have not been altered or corrupted during transmission across a public domain. This paper takes steps toward achieving full image transfer security within the Data Grid by utilizing DICOM image authentication and a HIPAA-compliant auditing system. The 3-D lossless digital signature embedding procedure involves a private 64 byte signature that is embedded into each original DICOM image volume, whereby on the receiving end the signature can to be extracted and verified following the DICOM transmission. This digital signature method has also been developed at the IPILab. The HIPAA-Compliant Auditing System (H-CAS) is required to monitor embedding and verification events, and allows monitoring of other grid activity as well. The H-CAS system federates the logs of transmission and authentication events at each grid-access-point and stores it into a HIPAA-compliant database. The auditing toolkit is installed at the local grid-access-point and utilizes Syslog [1], a client-server standard for log messaging over an IP network, to send messages to the H-CAS centralized database. By integrating digital image signatures and centralized logging capabilities, DICOM image integrity within the Medical Imaging and Informatics Data Grid can be monitored and guaranteed without loss to any image quality.

Designing a Multi-Petabyte Database for LSST

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

Becla, Jacek; Hanushevsky, Andrew; Nikolaev, Sergei

2007-01-10

The 3.2 giga-pixel LSST camera will produce approximately half a petabyte of archive images every month. These data need to be reduced in under a minute to produce real-time transient alerts, and then added to the cumulative catalog for further analysis. The catalog is expected to grow about three hundred terabytes per year. The data volume, the real-time transient alerting requirements of the LSST, and its spatio-temporal aspects require innovative techniques to build an efficient data access system at reasonable cost. As currently envisioned, the system will rely on a database for catalogs and metadata. Several database systems are beingmore » evaluated to understand how they perform at these data rates, data volumes, and access patterns. This paper describes the LSST requirements, the challenges they impose, the data access philosophy, results to date from evaluating available database technologies against LSST requirements, and the proposed database architecture to meet the data challenges.« less

Development of database system for data obtained by Hyper Suprime-Cam on Subaru Telescope

NASA Astrophysics Data System (ADS)

Yamada, Yoshihiko; Takata, Tadafumi; Furusawa, Hisanori; Okura, Yuki; Koike, Michitaro; Yamanoi, Hitomi; Mineo, Sogo; Yasuda, Naoki; Bickerton, Steve; Katayama, Nobuhiko; Lupton, Robert H.; Bosch, Jim; Loomis, Craig; Miyatake, Hironao; Price, Paul A.; Smith, Kendrick; Lang, Dustin

2014-08-01

Hyper Suprime-Cam (HSC) is the optical and near-infrared wide-field camera equipped on the Subaru Telescope. Its huge field of view (1.5 degree diameter) with 104 CCDs and the large mirror (8.2m) of the telescope will make us to study the Universe more efficiently. The analysis pipeline for HSC data produces processed images, and object catalogs of each CCD and stacked images. For survey in next 5 years, the number of rows in the object catalog table will reach to at least 5 x 109. We show the outline of the database systems of HSC data to store those huge data.

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.

Locating faces in color photographs using neural networks

NASA Astrophysics Data System (ADS)

Brown, Joe R.; Talley, Jim

1994-03-01

This paper summarizes a research effort in finding the locations and sizes of faces in color images (photographs, video stills, etc.) if, in fact, faces are presented. Scenarios for using such a system include serving as the means of localizing skin for automatic color balancing during photo processing or it could be used as a front-end in a customs port of energy context for a system which identified persona non grata given a database of known faces. The approach presented here is a hybrid system including: a neural pre-processor, some conventional image processing steps, and a neural classifier as the final face/non-face discriminator. Neither the training (containing 17,655 faces) nor the test (containing 1829 faces) imagery databases were constrained in their content or quality. The results for the pilot system are reported along with a discussion for improving the current system.

Multi-channel seismic reflection database for the northern Gulf of California, a highly-sedimented oblique rift

NASA Astrophysics Data System (ADS)

Steckler, M. S.; Haxby, W.; Persaud, P.; Stock, J.; Martín-Barajas, A.; Diebold, J.; Gonzalez-Fernandez, A.; Mountain, G. S.

2003-04-01

A multi-channel seismic reflection database has been developed to give access to high-resolution MCS data collected in the northern Gulf of California in May-June 1999. This data set consists of 3500 km of high-resolution MCS data acquired by the LDEO portable 48-channel MCS system using a 600-m streamer, a 1-ms sampling interval, and CDP spacing of 6.25/12.5 m on board the B/O Ulloa, the 28-m research vessel of CICESE. The resulting images have vertical resolution on the scale of meters to depths of up to 2 km below the seafloor. In addition, 48 sonobuoys recorded to 7 sec TWTT provided refraction velocities to greater depths. The northern Gulf of California is a transitional region between the oceanic ridge transform system of the central and southern Gulf and the continental San Andreas fault system of southern California. This data images the active deformation associated with the plate boundary zone in the northern Gulf of California. Multiple parallel rifts are simultaneously active in this wide complex zone of regional extension overprinted by shearing and a high sediment influx. The public-access database makes the cruise results, which is in a US MARGINS Program focus area, available to the broader geoscience community. The database includes navigation, final stacks and images for 80 seismic lines and 48 sonobuoys. The database may be accessed with MapApp, a downloadable Java application. Java applets offer many advantages over static or scripted web pages; they permit dynamic local interaction with data sets and limit time-consuming interaction with a remote server. MapApp displays the seismic lines on a map, and provides a viewer for inspecting images of the lines. Users may select a line from a list, or by clicking on the map. Once a line is selected, a user may load the image into the viewer, or download navigation, image or SEG-Y files. The viewer includes capability to zoom in and out, scroll, stretch or shrink horizontally, reverse direction, and toggle between black-on-white and white-on-black display. The section of the line in the viewer is indicated on the map, as is the current cursor location.

Automatic lung nodule graph cuts segmentation with deep learning false positive reduction

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang Bill; Qian, Wei

2017-03-01

To automatic detect lung nodules from CT images, we designed a two stage computer aided detection (CAD) system. The first stage is graph cuts segmentation to identify and segment the nodule candidates, and the second stage is convolutional neural network for false positive reduction. The dataset contains 595 CT cases randomly selected from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) and the 305 pulmonary nodules achieved diagnosis consensus by all four experienced radiologists were our detection targets. Consider each slice as an individual sample, 2844 nodules were included in our database. The graph cuts segmentation was conducted in a two-dimension manner, 2733 lung nodule ROIs are successfully identified and segmented. With a false positive reduction by a seven-layer convolutional neural network, 2535 nodules remain detected while the false positive dropped to 31.6%. The average F-measure of segmented lung nodule tissue is 0.8501.

A Web application for the management of clinical workflow in image-guided and adaptive proton therapy for prostate cancer treatments.

PubMed

Yeung, Daniel; Boes, Peter; Ho, Meng Wei; Li, Zuofeng

2015-05-08

Image-guided radiotherapy (IGRT), based on radiopaque markers placed in the prostate gland, was used for proton therapy of prostate patients. Orthogonal X-rays and the IBA Digital Image Positioning System (DIPS) were used for setup correction prior to treatment and were repeated after treatment delivery. Following a rationale for margin estimates similar to that of van Herk,(1) the daily post-treatment DIPS data were analyzed to determine if an adaptive radiotherapy plan was necessary. A Web application using ASP.NET MVC5, Entity Framework, and an SQL database was designed to automate this process. The designed features included state-of-the-art Web technologies, a domain model closely matching the workflow, a database-supporting concurrency and data mining, access to the DIPS database, secured user access and roles management, and graphing and analysis tools. The Model-View-Controller (MVC) paradigm allowed clean domain logic, unit testing, and extensibility. Client-side technologies, such as jQuery, jQuery Plug-ins, and Ajax, were adopted to achieve a rich user environment and fast response. Data models included patients, staff, treatment fields and records, correction vectors, DIPS images, and association logics. Data entry, analysis, workflow logics, and notifications were implemented. The system effectively modeled the clinical workflow and IGRT process.

Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

PubMed Central

Benammar Elgaaied, Amel; Cascio, Donato; Bruno, Salvatore; Ciaccio, Maria Cristina; Cipolla, Marco; Fauci, Alessandro; Morgante, Rossella; Taormina, Vincenzo; Gorgi, Yousr; Marrakchi Triki, Raja; Ben Ahmed, Melika; Louzir, Hechmi; Yalaoui, Sadok; Imene, Sfar; Issaoui, Yassine; Abidi, Ahmed; Ammar, Myriam; Bedhiafi, Walid; Ben Fraj, Oussama; Bouhaha, Rym; Hamdi, Khouloud; Soumaya, Koudhi; Neili, Bilel; Asma, Gati; Lucchese, Mariano; Catanzaro, Maria; Barbara, Vincenza; Brusca, Ignazio; Fregapane, Maria; Amato, Gaetano; Friscia, Giuseppe; Neila, Trai; Turkia, Souayeh; Youssra, Haouami; Rekik, Raja; Bouokez, Hayet; Vasile Simone, Maria; Fauci, Francesco; Raso, Giuseppe

2016-01-01

Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%). PMID:27042658

Noisy Ocular Recognition Based on Three Convolutional Neural Networks.

PubMed

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-12-17

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user's eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Sentence-Based Metadata: An Approach and Tool for Viewing Database Designs.

ERIC Educational Resources Information Center

Boyle, John M.; Gunge, Jakob; Bryden, John; Librowski, Kaz; Hanna, Hsin-Yi

2002-01-01

Describes MARS (Museum Archive Retrieval System), a research tool which enables organizations to exchange digital images and documents by means of a common thesaurus structure, and merge the descriptive data and metadata of their collections. Highlights include theoretical basis; searching the MARS database; and examples in European museums.…

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.

A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

NASA Technical Reports Server (NTRS)

Shapiro, Linda G.; Tanimoto, Steven L.; Ahrens, James P.

1996-01-01

The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

Named Entity Recognition in a Hungarian NL Based QA System

NASA Astrophysics Data System (ADS)

Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

Traffic Sign Inventory from Google Street View Images

NASA Astrophysics Data System (ADS)

Tsai, Victor J. D.; Chen, Jyun-Han; Huang, Hsun-Sheng

2016-06-01

Traffic sign detection and recognition (TSDR) has drawn considerable attention on developing intelligent transportation systems (ITS) and autonomous vehicle driving systems (AVDS) since 1980's. Unlikely to the general TSDR systems that deal with real-time images captured by the in-vehicle cameras, this research aims on developing techniques for detecting, extracting, and positioning of traffic signs from Google Street View (GSV) images along user-selected routes for low-cost, volumetric and quick establishment of the traffic sign infrastructural database that may be associated with Google Maps. The framework and techniques employed in the proposed system are described.

Explaining scene composition using kinematic chains of humans: application to Portuguese tiles history

NASA Astrophysics Data System (ADS)

da Silva, Nuno Pinho; Marques, Manuel; Carneiro, Gustavo; Costeira, João P.

2011-03-01

Painted tile panels (Azulejos) are one of the most representative Portuguese forms of art. Most of these panels are inspired on, and sometimes are literal copies of, famous paintings, or prints of those paintings. In order to study the Azulejos, art historians need to trace these roots. To do that they manually search art image databases, looking for images similar to the representation on the tile panel. This is an overwhelming task that should be automated as much as possible. Among several cues, the pose of humans and the general composition of people in a scene is quite discriminative. We build an image descriptor, combining the kinematic chain of each character, and contextual information about their composition, in the scene. Given a query image, our system computes its similarity profile over the database. Using nearest neighbors in the space of the descriptors, the proposed system retrieves the prints that most likely inspired the tiles' work.

Convolutional Neural Network-Based Shadow Detection in Images Using Visible Light Camera Sensor.

PubMed

Kim, Dong Seop; Arsalan, Muhammad; Park, Kang Ryoung

2018-03-23

Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detect and recognize the exact human area. Near-infrared (NIR) light cameras and thermal cameras are used to mitigate this problem. However, such instruments require a separate NIR illuminator, or are prohibitively expensive. Existing research on shadow detection in images captured by visible light cameras have utilized object and shadow color features for detection. Unfortunately, various environmental factors such as illumination change and brightness of background cause detection to be a difficult task. To overcome this problem, we propose a convolutional neural network-based shadow detection method. Experimental results with a database built from various outdoor surveillance camera environments, and from the context-aware vision using image-based active recognition (CAVIAR) open database, show that our method outperforms previous works.

Convolutional Neural Network-Based Shadow Detection in Images Using Visible Light Camera Sensor

PubMed Central

Kim, Dong Seop; Arsalan, Muhammad; Park, Kang Ryoung

2018-01-01

Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detect and recognize the exact human area. Near-infrared (NIR) light cameras and thermal cameras are used to mitigate this problem. However, such instruments require a separate NIR illuminator, or are prohibitively expensive. Existing research on shadow detection in images captured by visible light cameras have utilized object and shadow color features for detection. Unfortunately, various environmental factors such as illumination change and brightness of background cause detection to be a difficult task. To overcome this problem, we propose a convolutional neural network-based shadow detection method. Experimental results with a database built from various outdoor surveillance camera environments, and from the context-aware vision using image-based active recognition (CAVIAR) open database, show that our method outperforms previous works. PMID:29570690

Study on parallel and distributed management of RS data based on spatial data base

NASA Astrophysics Data System (ADS)

Chen, Yingbiao; Qian, Qinglan; Liu, Shijin

2006-12-01

With the rapid development of current earth-observing technology, RS image data storage, management and information publication become a bottle-neck for its appliance and popularization. There are two prominent problems in RS image data storage and management system. First, background server hardly handle the heavy process of great capacity of RS data which stored at different nodes in a distributing environment. A tough burden has put on the background server. Second, there is no unique, standard and rational organization of Multi-sensor RS data for its storage and management. And lots of information is lost or not included at storage. Faced at the above two problems, the paper has put forward a framework for RS image data parallel and distributed management and storage system. This system aims at RS data information system based on parallel background server and a distributed data management system. Aiming at the above two goals, this paper has studied the following key techniques and elicited some revelatory conclusions. The paper has put forward a solid index of "Pyramid, Block, Layer, Epoch" according to the properties of RS image data. With the solid index mechanism, a rational organization for different resolution, different area, different band and different period of Multi-sensor RS image data is completed. In data storage, RS data is not divided into binary large objects to be stored at current relational database system, while it is reconstructed through the above solid index mechanism. A logical image database for the RS image data file is constructed. In system architecture, this paper has set up a framework based on a parallel server of several common computers. Under the framework, the background process is divided into two parts, the common WEB process and parallel process.

Providing image management and communication functionality as an integral part of an existing hospital information system

NASA Astrophysics Data System (ADS)

Dayhoff, Ruth E.; Maloney, Daniel L.

1990-08-01

The effective delivery of health care has become increasingly dependent on a wide range of medical data which includes a variety of images. Manual and computer-based medical records ordinarily do not contain image data, leaving the physician to deal with a fragmented patient record widely scattered throughout the hospital. The Department of Veterans Affairs (VA) is currently installing a prototype hospital information system (HIS) workstation network to demonstrate the feasibility of providing image management and communications (IMAC) functionality as an integral part of an existing hospital information system. The core of this system is a database management system adapted to handle images as a new data type. A general model for this integration is discussed and specifics of the hospital-wide network of image display workstations are given.

Intelligent image capture of cartridge cases for firearms examiners

NASA Astrophysics Data System (ADS)

Jones, Brett C.; Guerci, Joseph R.

1997-02-01

The FBI's DRUGFIRETM system is a nationwide computerized networked image database of ballistic forensic evidence. This evidence includes images of cartridge cases and bullets obtained from both crime scenes and controlled test firings of seized weapons. Currently, the system is installed in over 80 forensic labs across the country and has enjoyed a high degree of success. In this paper, we discuss some of the issues and methods associated with providing a front-end semi-automated image capture system that simultaneously satisfies the often conflicting criteria of the many human examiners visual perception versus the criteria associated with optimizing autonomous digital image correlation. Specifically, we detail the proposed processing chain of an intelligent image capture system (IICS), involving a real- time capture 'assistant,' which assesses the quality of the image under test utilizing a custom designed neural network.

[Establishment of the database of the 3D facial models for the plastic surgery based on network].

PubMed

Liu, Zhe; Zhang, Hai-Lin; Zhang, Zheng-Guo; Qiao, Qun

2008-07-01

To collect the three-dimensional (3D) facial data of 30 facial deformity patients by the 3D scanner and establish a professional database based on Internet. It can be helpful for the clinical intervention. The primitive point data of face topography were collected by the 3D scanner. Then the 3D point cloud was edited by reverse engineering software to reconstruct the 3D model of the face. The database system was divided into three parts, including basic information, disease information and surgery information. The programming language of the web system is Java. The linkages between every table of the database are credibility. The query operation and the data mining are convenient. The users can visit the database via the Internet and use the image analysis system to observe the 3D facial models interactively. In this paper we presented a database and a web system adapt to the plastic surgery of human face. It can be used both in clinic and in basic research.

A mobile system for skin cancer diagnosis and monitoring

NASA Astrophysics Data System (ADS)

Gu, Yanliang; Tang, Jinshan

2014-05-01

In this paper, we propose a mobile system for aiding doctors in skin cancer diagnosis and other persons in skin cancer monitoring. The basic idea is to use image retrieval techniques to help the users to find the similar skin cancer cases stored in a database by using smart phones. The query image can be taken by a smart phone from a patient or can be uploaded from other resources. The shapes of the skin lesions are used for matching two skin lesions, which are segmented from skin images using the skin lesion extraction method developed in 1. The features used in the proposed system are obtained by Fourier descriptor. A prototype application has been developed and can be installed in an iPhone. In this application, the iPhone users can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.

Intelligent web image retrieval system

NASA Astrophysics Data System (ADS)

Hong, Sungyong; Lee, Chungwoo; Nah, Yunmook

2001-07-01

Recently, the web sites such as e-business sites and shopping mall sites deal with lots of image information. To find a specific image from these image sources, we usually use web search engines or image database engines which rely on keyword only retrievals or color based retrievals with limited search capabilities. This paper presents an intelligent web image retrieval system. We propose the system architecture, the texture and color based image classification and indexing techniques, and representation schemes of user usage patterns. The query can be given by providing keywords, by selecting one or more sample texture patterns, by assigning color values within positional color blocks, or by combining some or all of these factors. The system keeps track of user's preferences by generating user query logs and automatically add more search information to subsequent user queries. To show the usefulness of the proposed system, some experimental results showing recall and precision are also explained.

Digital Dental X-ray Database for Caries Screening

NASA Astrophysics Data System (ADS)

Rad, Abdolvahab Ehsani; Rahim, Mohd Shafry Mohd; Rehman, Amjad; Saba, Tanzila

2016-06-01

Standard database is the essential requirement to compare the performance of image analysis techniques. Hence the main issue in dental image analysis is the lack of available image database which is provided in this paper. Periapical dental X-ray images which are suitable for any analysis and approved by many dental experts are collected. This type of dental radiograph imaging is common and inexpensive, which is normally used for dental disease diagnosis and abnormalities detection. Database contains 120 various Periapical X-ray images from top to bottom jaw. Dental digital database is constructed to provide the source for researchers to use and compare the image analysis techniques and improve or manipulate the performance of each technique.

Partitioning medical image databases for content-based queries on a Grid.

PubMed

Montagnat, J; Breton, V; E Magnin, I

2005-01-01

In this paper we study the impact of executing a medical image database query application on the grid. For lowering the total computation time, the image database is partitioned into subsets to be processed on different grid nodes. A theoretical model of the application complexity and estimates of the grid execution overhead are used to efficiently partition the database. We show results demonstrating that smart partitioning of the database can lead to significant improvements in terms of total computation time. Grids are promising for content-based image retrieval in medical databases.

Palmprint identification using FRIT

NASA Astrophysics Data System (ADS)

Kisku, D. R.; Rattani, A.; Gupta, P.; Hwang, C. J.; Sing, J. K.

2011-06-01

This paper proposes a palmprint identification system using Finite Ridgelet Transform (FRIT) and Bayesian classifier. FRIT is applied on the ROI (region of interest), which is extracted from palmprint image, to extract a set of distinctive features from palmprint image. These features are used to classify with the help of Bayesian classifier. The proposed system has been tested on CASIA and IIT Kanpur palmprint databases. The experimental results reveal better performance compared to all well known systems.

Geographic Information System Data Analysis

NASA Technical Reports Server (NTRS)

Billings, Chad; Casad, Christopher; Floriano, Luis G.; Hill, Tracie; Johnson, Rashida K.; Locklear, J. Mark; Penn, Stephen; Rhoulac, Tori; Shay, Adam H.; Taylor, Antone;

Recognition of blurred images by the method of moments.

PubMed

Flusser, J; Suk, T; Saic, S

1996-01-01

The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.

A Study of NetCDF as an Approach for High Performance Medical Image Storage

NASA Astrophysics Data System (ADS)

Magnus, Marcone; Coelho Prado, Thiago; von Wangenhein, Aldo; de Macedo, Douglas D. J.; Dantas, M. A. R.

2012-02-01

The spread of telemedicine systems increases every day. The systems and PACS based on DICOM images has become common. This rise reflects the need to develop new storage systems, more efficient and with lower computational costs. With this in mind, this article discusses a study for application in NetCDF data format as the basic platform for storage of DICOM images. The study case comparison adopts an ordinary database, the HDF5 and the NetCDF to storage the medical images. Empirical results, using a real set of images, indicate that the time to retrieve images from the NetCDF for large scale images has a higher latency compared to the other two methods. In addition, the latency is proportional to the file size, which represents a drawback to a telemedicine system that is characterized by a large amount of large image files.

Research and development of web oriented remote sensing image publication system based on Servlet technique

NASA Astrophysics Data System (ADS)

Juanle, Wang; Shuang, Li; Yunqiang, Zhu

2005-10-01

According to the requirements of China National Scientific Data Sharing Program (NSDSP), the research and development of web oriented RS Image Publication System (RSIPS) is based on Java Servlet technique. The designing of RSIPS framework is composed of 3 tiers, which is Presentation Tier, Application Service Tier and Data Resource Tier. Presentation Tier provides user interface for data query, review and download. For the convenience of users, visual spatial query interface is included. Served as a middle tier, Application Service Tier controls all actions between users and databases. Data Resources Tier stores RS images in file and relationship databases. RSIPS is developed with cross platform programming based on Java Servlet tools, which is one of advanced techniques in J2EE architecture. RSIPS's prototype has been developed and applied in the geosciences clearinghouse practice which is among the experiment units of NSDSP in China.

An automated image-collection system for crystallization experiments using SBS standard microplates.

PubMed

Brostromer, Erik; Nan, Jie; Su, Xiao Dong

2007-02-01

As part of a structural genomics platform in a university laboratory, a low-cost in-house-developed automated imaging system for SBS microplate experiments has been designed and constructed. The imaging system can scan a microplate in 2-6 min for a 96-well plate depending on the plate layout and scanning options. A web-based crystallization database system has been developed, enabling users to follow their crystallization experiments from a web browser. As the system has been designed and built by students and crystallographers using commercially available parts, this report is aimed to serve as a do-it-yourself example for laboratory robotics.

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.

Casimage project: a digital teaching files authoring environment.

PubMed

Rosset, Antoine; Muller, Henning; Martins, Martina; Dfouni, Natalia; Vallée, Jean-Paul; Ratib, Osman

2004-04-01

The goal of the Casimage project is to offer an authoring and editing environment integrated with the Picture Archiving and Communication Systems (PACS) for creating image-based electronic teaching files. This software is based on a client/server architecture allowing remote access of users to a central database. This authoring environment allows radiologists to create reference databases and collection of digital images for teaching and research directly from clinical cases being reviewed on PACS diagnostic workstations. The environment includes all tools to create teaching files, including textual description, annotations, and image manipulation. The software also allows users to generate stand-alone CD-ROMs and web-based teaching files to easily share their collections. The system includes a web server compatible with the Medical Imaging Resource Center standard (MIRC, http://mirc.rsna.org) to easily integrate collections in the RSNA web network dedicated to teaching files. This software could be installed on any PACS workstation to allow users to add new cases at any time and anywhere during clinical operations. Several images collections were created with this tool, including thoracic imaging that was subsequently made available on a CD-Rom and on our web site and through the MIRC network for public access.

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.

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Collection of sequential imaging events for research in breast cancer screening

NASA Astrophysics Data System (ADS)

Patel, M. N.; Young, K.; Halling-Brown, M. D.

2016-03-01

Due to the huge amount of research involving medical images, there is a widely accepted need for comprehensive collections of medical images to be made available for research. This demand led to the design and implementation of a flexible image repository, which retrospectively collects images and data from multiple sites throughout the UK. The OPTIMAM Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, annotations and expert-determined ground truths. Collection has been ongoing for over three years, providing the opportunity to collect sequential imaging events. Extensive alterations to the identification, collection, processing and storage arms of the system have been undertaken to support the introduction of sequential events, including interval cancers. These updates to the collection systems allow the acquisition of many more images, but more importantly, allow one to build on the existing high-dimensional data stored in the OMI-DB. A research dataset of this scale, which includes original normal and subsequent malignant cases along with expert derived and clinical annotations, is currently unique. These data provide a powerful resource for future research and has initiated new research projects, amongst which, is the quantification of normal cases by applying a large number of quantitative imaging features, with a priori knowledge that eventually these cases develop a malignancy. This paper describes, extensions to the OMI-DB collection systems and tools and discusses the prospective applications of having such a rich dataset for future research applications.

Study on Big Database Construction and its Application of Sample Data Collected in CHINA'S First National Geographic Conditions Census Based on Remote Sensing Images

NASA Astrophysics Data System (ADS)

Cheng, T.; Zhou, X.; Jia, Y.; Yang, G.; Bai, J.

2018-04-01

In the project of China's First National Geographic Conditions Census, millions of sample data have been collected all over the country for interpreting land cover based on remote sensing images, the quantity of data files reaches more than 12,000,000 and has grown in the following project of National Geographic Conditions Monitoring. By now, using database such as Oracle for storing the big data is the most effective method. However, applicable method is more significant for sample data's management and application. This paper studies a database construction method which is based on relational database with distributed file system. The vector data and file data are saved in different physical location. The key issues and solution method are discussed. Based on this, it studies the application method of sample data and analyzes some kinds of using cases, which could lay the foundation for sample data's application. Particularly, sample data locating in Shaanxi province are selected for verifying the method. At the same time, it takes 10 first-level classes which defined in the land cover classification system for example, and analyzes the spatial distribution and density characteristics of all kinds of sample data. The results verify that the method of database construction which is based on relational database with distributed file system is very useful and applicative for sample data's searching, analyzing and promoted application. Furthermore, sample data collected in the project of China's First National Geographic Conditions Census could be useful in the earth observation and land cover's quality assessment.

Advanced Technologies for the Study of Earth Systems.

ERIC Educational Resources Information Center

Sproull, Jim

1991-01-01

Describes the Joint Education Initiative (JEdI) project designed to instruct teachers how to access scientific data and images for classroom instruction. Presents a sample CD-ROM classroom computer activity that illustrates how CD images and databases can be combined for a science investigation comparing topography to gravity anomalies. (MCO)

The Descriptive Challenges of Fiber Art.

ERIC Educational Resources Information Center

Lunin, Lois F.

1990-01-01

A definition of fiber art, its history, materials and techniques, vocabularies, and creators and users of those vocabularies offer background for understanding the problems in preparing surrogates of this relatively recent art form for text and image databases. Four examples of fiber image information systems are described. (32 references) (EAM)

Method of preliminary localization of the iris in biometric access control systems

NASA Astrophysics Data System (ADS)

Minacova, N.; Petrov, I.

2015-10-01

This paper presents a method of preliminary localization of the iris, based on the stable brightness features of the iris in images of the eye. In tests on images of eyes from publicly available databases method showed good accuracy and speed compared to existing methods preliminary localization.

Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit/hyperactivity disorder? Analysis with brain-image database

NASA Technical Reports Server (NTRS)

Herskovits, E. H.; Megalooikonomou, V.; Davatzikos, C.; Chen, A.; Bryan, R. N.; Gerring, J. P.

1999-01-01

PURPOSE: To determine whether there is an association between the spatial distribution of lesions detected at magnetic resonance (MR) imaging of the brain in children after closed-head injury and the development of secondary attention-deficit/hyperactivity disorder (ADHD). MATERIALS AND METHODS: Data obtained from 76 children without prior history of ADHD were analyzed. MR images were obtained 3 months after closed-head injury. After manual delineation of lesions, images were registered to the Talairach coordinate system. For each subject, registered images and secondary ADHD status were integrated into a brain-image database, which contains depiction (visualization) and statistical analysis software. Using this database, we assessed visually the spatial distributions of lesions and performed statistical analysis of image and clinical variables. RESULTS: Of the 76 children, 15 developed secondary ADHD. Depiction of the data suggested that children who developed secondary ADHD had more lesions in the right putamen than children who did not develop secondary ADHD; this impression was confirmed statistically. After Bonferroni correction, we could not demonstrate significant differences between secondary ADHD status and lesion burdens for the right caudate nucleus or the right globus pallidus. CONCLUSION: Closed-head injury-induced lesions in the right putamen in children are associated with subsequent development of secondary ADHD. Depiction software is useful in guiding statistical analysis of image data.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Biometric analysis of the palm vein distribution by means two different techniques of feature extraction

NASA Astrophysics Data System (ADS)

Castro-Ortega, R.; Toxqui-Quitl, C.; Solís-Villarreal, J.; Padilla-Vivanco, A.; Castro-Ramos, J.

2014-09-01

Vein patterns can be used for accessing, identifying, and authenticating purposes; which are more reliable than classical identification way. Furthermore, these patterns can be used for venipuncture in health fields to get on to veins of patients when they cannot be seen with the naked eye. In this paper, an image acquisition system is implemented in order to acquire digital images of people hands in the near infrared. The image acquisition system consists of a CCD camera and a light source with peak emission in the 880 nm. This radiation can penetrate and can be strongly absorbed by the desoxyhemoglobin that is presented in the blood of the veins. Our method of analysis is composed by several steps and the first one of all is the enhancement of acquired images which is implemented by spatial filters. After that, adaptive thresholding and mathematical morphology operations are used in order to obtain the distribution of vein patterns. The above process is focused on the people recognition through of images of their palm-dorsal distributions obtained from the near infrared light. This work has been directed for doing a comparison of two different techniques of feature extraction as moments and veincode. The classification task is achieved using Artificial Neural Networks. Two databases are used for the analysis of the performance of the algorithms. The first database used here is owned of the Hong Kong Polytechnic University and the second one is our own database.

The Design of a High Performance Earth Imagery and Raster Data Management and Processing Platform

NASA Astrophysics Data System (ADS)

Xie, Qingyun

2016-06-01

This paper summarizes the general requirements and specific characteristics of both geospatial raster database management system and raster data processing platform from a domain-specific perspective as well as from a computing point of view. It also discusses the need of tight integration between the database system and the processing system. These requirements resulted in Oracle Spatial GeoRaster, a global scale and high performance earth imagery and raster data management and processing platform. The rationale, design, implementation, and benefits of Oracle Spatial GeoRaster are described. Basically, as a database management system, GeoRaster defines an integrated raster data model, supports image compression, data manipulation, general and spatial indices, content and context based queries and updates, versioning, concurrency, security, replication, standby, backup and recovery, multitenancy, and ETL. It provides high scalability using computer and storage clustering. As a raster data processing platform, GeoRaster provides basic operations, image processing, raster analytics, and data distribution featuring high performance computing (HPC). Specifically, HPC features include locality computing, concurrent processing, parallel processing, and in-memory computing. In addition, the APIs and the plug-in architecture are discussed.

Quantitative approach for optimizing e-beam condition of photoresist inspection and measurement

NASA Astrophysics Data System (ADS)

Lin, Chia-Jen; Teng, Chia-Hao; Cheng, Po-Chung; Sato, Yoshishige; Huang, Shang-Chieh; Chen, Chu-En; Maruyama, Kotaro; Yamazaki, Yuichiro

2018-03-01

Severe process margin in advanced technology node of semiconductor device is controlled by e-beam metrology system and e-beam inspection system with scanning electron microscopy (SEM) image. By using SEM, larger area image with higher image quality is required to collect massive amount of data for metrology and to detect defect in a large area for inspection. Although photoresist is the one of the critical process in semiconductor device manufacturing, observing photoresist pattern by SEM image is crucial and troublesome especially in the case of large image. The charging effect by e-beam irradiation on photoresist pattern causes deterioration of image quality, and it affect CD variation on metrology system and causes difficulties to continue defect inspection in a long time for a large area. In this study, we established a quantitative approach for optimizing e-beam condition with "Die to Database" algorithm of NGR3500 on photoresist pattern to minimize charging effect. And we enhanced the performance of measurement and inspection on photoresist pattern by using optimized e-beam condition. NGR3500 is the geometry verification system based on "Die to Database" algorithm which compares SEM image with design data [1]. By comparing SEM image and design data, key performance indicator (KPI) of SEM image such as "Sharpness", "S/N", "Gray level variation in FOV", "Image shift" can be retrieved. These KPIs were analyzed with different e-beam conditions which consist of "Landing Energy", "Probe Current", "Scanning Speed" and "Scanning Method", and the best e-beam condition could be achieved with maximum image quality, maximum scanning speed and minimum image shift. On this quantitative approach of optimizing e-beam condition, we could observe dependency of SEM condition on photoresist charging. By using optimized e-beam condition, measurement could be continued on photoresist pattern over 24 hours stably. KPIs of SEM image proved image quality during measurement and inspection was stabled enough.

A client/server system for Internet access to biomedical text/image databanks.

PubMed

Thoma, G R; Long, L R; Berman, L E

1996-01-01

Internet access to mixed text/image databanks is finding application in the medical world. An example is a database of medical X-rays and associated data consisting of demographic, socioeconomic, physician's exam, medical laboratory and other information collected as part of a nationwide health survey conducted by the government. Another example is a collection of digitized cryosection images, CT and MR taken of cadavers as part of the National Library of Medicine's Visible Human Project. In both cases, the challenge is to provide access to both the image and the associated text for a wide end user community to create atlases, conduct epidemiological studies, to develop image-specific algorithms for compression, enhancement and other types of image processing, among many other applications. The databanks mentioned above are being created in prototype form. This paper describes the prototype system developed for the archiving of the data and the client software to enable a broad range of end users to access the archive, retrieve text and image data, display the data and manipulate the images. System design considerations include; data organization in a relational database management system with object-oriented extensions; a hierarchical organization of the image data by different resolution levels for different user classes; client design based on common hardware and software platforms incorporating SQL search capability, X Window, Motif and TAE (a development environment supporting rapid prototyping and management of graphic-oriented user interfaces); potential to include ultra high resolution display monitors as a user option; intuitive user interface paradigm for building complex queries; and contrast enhancement, magnification and mensuration tools for better viewing by the user.

Artist Material BRDF Database for Computer Graphics Rendering

NASA Astrophysics Data System (ADS)

Ashbaugh, Justin C.

The primary goal of this thesis was to create a physical library of artist material samples. This collection provides necessary data for the development of a gonio-imaging system for use in museums to more accurately document their collections. A sample set was produced consisting of 25 panels and containing nearly 600 unique samples. Selected materials are representative of those commonly used by artists both past and present. These take into account the variability in visual appearance resulting from the materials and application techniques used. Five attributes of variability were identified including medium, color, substrate, application technique and overcoat. Combinations of these attributes were selected based on those commonly observed in museum collections and suggested by surveying experts in the field. For each sample material, image data is collected and used to measure an average bi-directional reflectance distribution function (BRDF). The results are available as a public-domain image and optical database of artist materials at art-si.org. Additionally, the database includes specifications for each sample along with other information useful for computer graphics rendering such as the rectified sample images and normal maps.

Studying the Sky/Planets Can Drown You in Images: Machine Learning Solutions at JPL/Caltech

NASA Technical Reports Server (NTRS)

Fayyad, U. M.

1995-01-01

JPL is working to develop a domain-independent system capable of small-scale object recognition in large image databases for science analysis. Two applications discussed are the cataloging of three billion sky objects in the Sky Image Cataloging and Analysis Tool (SKICAT) and the detection of possibly one million small volcanoes visible in the Magellan synthetic aperture radar images of Venus (JPL Adaptive Recognition Tool, JARTool).

DICOM image integration into an electronic medical record using thin viewing clients

NASA Astrophysics Data System (ADS)

Stewart, Brent K.; Langer, Steven G.; Taira, Ricky K.

1998-07-01

Purpose -- To integrate radiological DICOM images into our currently existing web-browsable Electronic Medical Record (MINDscape). Over the last five years the University of Washington has created a clinical data repository combining in a distributed relational database information from multiple departmental databases (MIND). A text-based view of this data called the Mini Medical Record (MMR) has been available for three years. MINDscape, unlike the text based MMR, provides a platform independent, web browser view of the MIND dataset that can easily be linked to other information resources on the network. We have now added the integration of radiological images into MINDscape through a DICOM webserver. Methods/New Work -- we have integrated a commercial webserver that acts as a DICOM Storage Class Provider to our, computed radiography (CR), computed tomography (CT), digital fluoroscopy (DF), magnetic resonance (MR) and ultrasound (US) scanning devices. These images can be accessed through CGI queries or by linking the image server database using ODBC or SQL gateways. This allows the use of dynamic HTML links to the images on the DICOM webserver from MINDscape, so that the radiology reports already resident in the MIND repository can be married with the associated images through the unique examination accession number generated by our Radiology Information System (RIS). The web browser plug-in used provides a wavelet decompression engine (up to 16-bits per pixel) and performs the following image manipulation functions: window/level, flip, invert, sort, rotate, zoom, cine-loop and save as JPEG. Results -- Radiological DICOM image sets (CR, CT, MR and US) are displayed with associated exam reports for referring physician and clinicians anywhere within the widespread academic medical center on PCs, Macs, X-terminals and Unix computers. This system is also being used for home teleradiology application. Conclusion -- Radiological DICOM images can be made available medical center wide to physicians quickly using low-cost and ubiquitous, thin client browsing technology and wavelet compression.

TU-F-CAMPUS-I-05: Semi-Automated, Open Source MRI Quality Assurance and Quality Control Program for Multi-Unit Institution

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

Yung, J; Stefan, W; Reeve, D

2015-06-15

Purpose: Phantom measurements allow for the performance of magnetic resonance (MR) systems to be evaluated. Association of Physicists in Medicine (AAPM) Report No. 100 Acceptance Testing and Quality Assurance Procedures for MR Imaging Facilities, American College of Radiology (ACR) MR Accreditation Program MR phantom testing, and ACR MRI quality control (QC) program documents help to outline specific tests for establishing system performance baselines as well as system stability over time. Analyzing and processing tests from multiple systems can be time-consuming for medical physicists. Besides determining whether tests are within predetermined limits or criteria, monitoring longitudinal trends can also help preventmore » costly downtime of systems during clinical operation. In this work, a semi-automated QC program was developed to analyze and record measurements in a database that allowed for easy access to historical data. Methods: Image analysis was performed on 27 different MR systems of 1.5T and 3.0T field strengths from GE and Siemens manufacturers. Recommended measurements involved the ACR MRI Accreditation Phantom, spherical homogenous phantoms, and a phantom with an uniform hole pattern. Measurements assessed geometric accuracy and linearity, position accuracy, image uniformity, signal, noise, ghosting, transmit gain, center frequency, and magnetic field drift. The program was designed with open source tools, employing Linux, Apache, MySQL database and Python programming language for the front and backend. Results: Processing time for each image is <2 seconds. Figures are produced to show regions of interests (ROIs) for analysis. Historical data can be reviewed to compare previous year data and to inspect for trends. Conclusion: A MRI quality assurance and QC program is necessary for maintaining high quality, ACR MRI Accredited MR programs. A reviewable database of phantom measurements assists medical physicists with processing and monitoring of large datasets. Longitudinal data can reveal trends that although are within passing criteria indicate underlying system issues.« less

Normal Databases for the Relative Quantification of Myocardial Perfusion

PubMed Central

Rubeaux, Mathieu; Xu, Yuan; Germano, Guido; Berman, Daniel S.; Slomka, Piotr J.

2016-01-01

Purpose of review Myocardial perfusion imaging (MPI) with SPECT is performed clinically worldwide to detect and monitor coronary artery disease (CAD). MPI allows an objective quantification of myocardial perfusion at stress and rest. This established technique relies on normal databases to compare patient scans against reference normal limits. In this review, we aim to introduce the process of MPI quantification with normal databases and describe the associated perfusion quantitative measures that are used. Recent findings New equipment and new software reconstruction algorithms have been introduced which require the development of new normal limits. The appearance and regional count variations of normal MPI scan may differ between these new scanners and standard Anger cameras. Therefore, these new systems may require the determination of new normal limits to achieve optimal accuracy in relative myocardial perfusion quantification. Accurate diagnostic and prognostic results rivaling those obtained by expert readers can be obtained by this widely used technique. Summary Throughout this review, we emphasize the importance of the different normal databases and the need for specific databases relative to distinct imaging procedures. use of appropriate normal limits allows optimal quantification of MPI by taking into account subtle image differences due to the hardware and software used, and the population studied. PMID:28138354

A comparison of basic deinterlacing approaches for a computer assisted diagnosis approach of videoscope images

NASA Astrophysics Data System (ADS)

Kage, Andreas; Canto, Marcia; Gorospe, Emmanuel; Almario, Antonio; Münzenmayer, Christian

2010-03-01

In the near future, Computer Assisted Diagnosis (CAD) which is well known in the area of mammography might be used to support clinical experts in the diagnosis of images derived from imaging modalities such as endoscopy. In the recent past, a few first approaches for computer assisted endoscopy have been presented already. These systems use a video signal as an input that is provided by the endoscopes video processor. Despite the advent of high-definition systems most standard endoscopy systems today still provide only analog video signals. These signals consist of interlaced images that can not be used in a CAD approach without deinterlacing. Of course, there are many different deinterlacing approaches known today. But most of them are specializations of some basic approaches. In this paper we present four basic deinterlacing approaches. We have used a database of non-interlaced images which have been degraded by artificial interlacing and afterwards processed by these approaches. The database contains regions of interest (ROI) of clinical relevance for the diagnosis of abnormalities in the esophagus. We compared the classification rates on these ROIs on the original images and after the deinterlacing. The results show that the deinterlacing has an impact on the classification rates. The Bobbing approach and the Motion Compensation approach achieved the best classification results in most cases.

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.

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.

PubMed

Chi, Jianning; Walia, Ekta; Babyn, Paul; Wang, Jimmy; Groot, Gary; Eramian, Mark

2017-08-01

With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features from thyroid ultrasound images. Ultrasound images are pre-processed to calibrate their scale and remove the artifacts. A pre-trained GoogLeNet model is then fine-tuned using the pre-processed image samples which leads to superior feature extraction. The extracted features of the thyroid ultrasound images are sent to a Cost-sensitive Random Forest classifier to classify the images into "malignant" and "benign" cases. The experimental results show the proposed fine-tuned GoogLeNet model achieves excellent classification performance, attaining 98.29% classification accuracy, 99.10% sensitivity and 93.90% specificity for the images in an open access database (Pedraza et al. 16), while 96.34% classification accuracy, 86% sensitivity and 99% specificity for the images in our local health region database.

Success of HIS DICOM interfaces in the integration of the healthcare enterprise at the Department of Veterans Affairs

NASA Astrophysics Data System (ADS)

Kuzmak, Peter M.; Dayhoff, Ruth E.

1999-07-01

The US Department of Veterans Affairs (VA) is integrating imaging into the healthcare enterprise using the Digital Imaging and Communication in Medicine (DICOM) standard protocols. Image management is directly integrated into the VistA Hospital Information System (HIS) software and the clinical database. Radiology images are acquired via DICOM, and are stored directly in the HIS database. Images can be displayed on low-cost clinician's workstations throughout the medical center. High-resolution diagnostic quality multi-monitor VistA workstations with specialized viewing software can be used for reading radiology images. Two approaches are used to acquire and handle imags within the radiology department. Some sties have a commercial Picture Archiving and Communications System (PACS) interfaced to the VistA HIS, while other sites use the direct image acquisition and integrated diagnostic reading capabilities of VistA itself. A small set of DICOM services have been implemented by VistA to allow patient and study text data to be transmitted to image producing modalities and the commercial PACS, and to enable images and study data to be transferred back. The VistA DICOM capabilities are now used to interface seven different commercial PACS products and over twenty different radiology modalities. The communications capabilities of DICOM and the VA wide area network are begin used to support reading of radiology images form remote sites. DICOM has been the cornerstone in the ability to integrate imaging functionality into the Healthcare Enterprise. Because of its openness, it allows the integration of system component from commercial and non- commercial sources to work together to provide functional cost-effective solutions. As DICOM expands to non-radiology devices, integration must occur with the specialty information subsystems that handle orders and reports, their associated DICOM image capture systems, and the computer- based patient record. The mode and concepts of the DICOM standard can be extended to these other areas, but some adjustments may be required.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

PubMed Central

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-01-01

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods. PMID:29258217

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.

A Multimedia Database Management System Supporting Contents Search in Media Data

DTIC Science & Technology

1989-03-01

predicates: car (x), manufacturer (x, Horch ), year-built (x, 1922) to designate that the car was manufactured by Horch in the year 1922. The use of the name...manufacturer (imagel, x, " Horch "). year-built (imagel, x, 1922). query(I) :- car (I, Z), manufacturer (I, Z, " Horch "). ?- query(Image). yes. Image = image... Horch ) : imageJ 1, imageJ2, etc. In certain cases a predicate may generate entries in more than one list. For example, if the predicate of action

Filmless PACS in a multiple facility environment

NASA Astrophysics Data System (ADS)

Wilson, Dennis L.; Glicksman, Robert A.; Prior, Fred W.; Siu, Kai-Yeung; Goldburgh, Mitchell M.

1996-05-01

A Picture Archiving and Communication System centered on a shared image file server can support a filmless hospital. Systems based on this architecture have proven themselves in over four years of clinical operation. Changes in healthcare delivery are causing radiology groups to support multiple facilities for remote clinic support and consolidation of services. There will be a corresponding need for communicating over a standardized wide area network (WAN). Interactive workflow, a natural extension to the single facility case, requires a means to work effectively and seamlessly across moderate to low speed communication networks. Several schemes for supporting a consortium of medical treatment facilities over a WAN are explored. Both centralized and distributed database approaches are evaluated against several WAN scenarios. Likewise, several architectures for distributing image file servers or buffers over a WAN are explored, along with the caching and distribution strategies that support them. An open system implementation is critical to the success of a wide area system. The role of the Digital Imaging and Communications in Medicine (DICOM) standard in supporting multi- facility and multi-vendor open systems is also addressed. An open system can be achieved by using a DICOM server to provide a view of the system-wide distributed database. The DICOM server interface to a local version of the global database lets a local workstation treat the multiple, distributed data servers as though they were one local server for purposes of examination queries. The query will recover information about the examination that will permit retrieval over the network from the server on which the examination resides. For efficiency reasons, the ability to build cross-facility radiologist worklists and clinician-oriented patient folders is essential. The technologies of the World-Wide-Web can be used to generate worklists and patient folders across facilities. A reliable broadcast protocol may be a convenient way to notify many different users and many image servers about new activities in the network of image servers. In addition to ensuring reliability of message delivery and global serialization of each broadcast message in the network, the broadcast protocol should not introduce significant communication overhead.

Diagnostic report acquisition unit for the Mayo/IBM PACS project

NASA Astrophysics Data System (ADS)

Brooks, Everett G.; Rothman, Melvyn L.

1991-07-01

The Mayo Clinic and IBM Rochester have jointly developed a picture archive and control system (PACS) for use with Mayo's MRI and Neuro-CT imaging modalities. One of the challenges of developing a useful PACS involves integrating the diagnostic reports with the electronic images so they can be displayed simultaneously. By the time a diagnostic report is generated for a particular case, its images have already been captured and archived by the PACS. To integrate the report with the images, the authors have developed an IBM Personal System/2 computer (PS/2) based diagnostic report acquisition unit (RAU). A typed copy of the report is transmitted via facsimile to the RAU where it is stacked electronically with other reports that have been sent previously but not yet processed. By processing these reports at the RAU, the information they contain is integrated with the image database and a copy of the report is archived electronically on an IBM Application System/400 computer (AS/400). When a user requests a set of images for viewing, the report is automatically integrated with the image data. By using a hot key, the user can toggle on/off the report on the display screen. This report describes process, hardware, and software employed to integrate the diagnostic report information into the PACS, including how the report images are captured, transmitted, and entered into the AS/400 database. Also described is how the archived reports and their associated medical images are located and merged for retrieval and display. The methods used to detect and process error conditions are also discussed.

Normative Databases for Imaging Instrumentation.

PubMed

Realini, Tony; Zangwill, Linda M; Flanagan, John G; Garway-Heath, David; Patella, Vincent M; Johnson, Chris A; Artes, Paul H; Gaddie, Ian B; Fingeret, Murray

2015-08-01

To describe the process by which imaging devices undergo reference database development and regulatory clearance. The limitations and potential improvements of reference (normative) data sets for ophthalmic imaging devices will be discussed. A symposium was held in July 2013 in which a series of speakers discussed issues related to the development of reference databases for imaging devices. Automated imaging has become widely accepted and used in glaucoma management. The ability of such instruments to discriminate healthy from glaucomatous optic nerves, and to detect glaucomatous progression over time is limited by the quality of reference databases associated with the available commercial devices. In the absence of standardized rules governing the development of reference databases, each manufacturer's database differs in size, eligibility criteria, and ethnic make-up, among other key features. The process for development of imaging reference databases may be improved by standardizing eligibility requirements and data collection protocols. Such standardization may also improve the degree to which results may be compared between commercial instruments.

Normative Databases for Imaging Instrumentation

PubMed Central

Realini, Tony; Zangwill, Linda; Flanagan, John; Garway-Heath, David; Patella, Vincent Michael; Johnson, Chris; Artes, Paul; Ben Gaddie, I.; Fingeret, Murray

2015-01-01

Purpose To describe the process by which imaging devices undergo reference database development and regulatory clearance. The limitations and potential improvements of reference (normative) data sets for ophthalmic imaging devices will be discussed. Methods A symposium was held in July 2013 in which a series of speakers discussed issues related to the development of reference databases for imaging devices. Results Automated imaging has become widely accepted and used in glaucoma management. The ability of such instruments to discriminate healthy from glaucomatous optic nerves, and to detect glaucomatous progression over time is limited by the quality of reference databases associated with the available commercial devices. In the absence of standardized rules governing the development of reference databases, each manufacturer’s database differs in size, eligibility criteria, and ethnic make-up, among other key features. Conclusions The process for development of imaging reference databases may be improved by standardizing eligibility requirements and data collection protocols. Such standardization may also improve the degree to which results may be compared between commercial instruments. PMID:25265003

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

Distributed Database Control and Allocation. Volume 1. Frameworks for Understanding Concurrency Control and Recovery Algorithms.

DTIC Science & Technology

1983-10-01

an Aborti , It forwards the operation directly to the recovery system. When the recovery system acknowledges that the operation has been processed, the...list... AbortI . rite Ti Into the abort list. Then undo all of Ti’s writes by reedina their bet ore-images from the audit trail and writin. them back...Into the stable database. [Ack) Then, delete Ti from the active list. Restart. Process Aborti for each Ti on the active list. Ack) In this algorithm

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Mapping Indigenous Depth of Place

ERIC Educational Resources Information Center

Pearce, Margaret Wickens; Louis, Renee Pualani

2008-01-01

Indigenous communities have successfully used Western geospatial technologies (GT) (for example, digital maps, satellite images, geographic information systems (GIS), and global positioning systems (GPS)) since the 1970s to protect tribal resources, document territorial sovereignty, create tribal utility databases, and manage watersheds. The use…

78 FR 70020 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-22

...; citizenship; physical characteristics; employment and military service history; credit references and credit... digital images, and in electronic databases. Background investigation forms are maintained in the...

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PubMed

Kalpathy-Cramer, Jayashree; Campbell, J Peter; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Manchester visual query language

NASA Astrophysics Data System (ADS)

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

1993-04-01

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

Appropriateness of the food-pics image database for experimental eating and appetite research with adolescents.

PubMed

Jensen, Chad D; Duraccio, Kara M; Barnett, Kimberly A; Stevens, Kimberly S

2016-12-01

Research examining effects of visual food cues on appetite-related brain processes and eating behavior has proliferated. Recently investigators have developed food image databases for use across experimental studies examining appetite and eating behavior. The food-pics image database represents a standardized, freely available image library originally validated in a large sample primarily comprised of adults. The suitability of the images for use with adolescents has not been investigated. The aim of the present study was to evaluate the appropriateness of the food-pics image library for appetite and eating research with adolescents. Three hundred and seven adolescents (ages 12-17) provided ratings of recognizability, palatability, and desire to eat, for images from the food-pics database. Moreover, participants rated the caloric content (high vs. low) and healthiness (healthy vs. unhealthy) of each image. Adolescents rated approximately 75% of the food images as recognizable. Approximately 65% of recognizable images were correctly categorized as high vs. low calorie and 63% were correctly classified as healthy vs. unhealthy in 80% or more of image ratings. These results suggest that a smaller subset of the food-pics image database is appropriate for use with adolescents. With some modifications to included images, the food-pics image database appears to be appropriate for use in experimental appetite and eating-related research conducted with adolescents. Copyright © 2016 Elsevier Ltd. All rights reserved.

A completely automated CAD system for mass detection in a large mammographic database.

PubMed

Bellotti, R; De Carlo, F; Tangaro, S; Gargano, G; Maggipinto, G; Castellano, M; Massafra, R; Cascio, D; Fauci, F; Magro, R; Raso, G; Lauria, A; Forni, G; Bagnasco, S; Cerello, P; Zanon, E; Cheran, S C; Lopez Torres, E; Bottigli, U; Masala, G L; Oliva, P; Retico, A; Fantacci, M E; Cataldo, R; De Mitri, I; De Nunzio, G

2006-08-01

Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.

New generic indexing technology

NASA Technical Reports Server (NTRS)

Freeston, Michael

1996-01-01

There has been no fundamental change in the dynamic indexing methods supporting database systems since the invention of the B-tree twenty-five years ago. And yet the whole classical approach to dynamic database indexing has long since become inappropriate and increasingly inadequate. We are moving rapidly from the conventional one-dimensional world of fixed-structure text and numbers to a multi-dimensional world of variable structures, objects and images, in space and time. But, even before leaving the confines of conventional database indexing, the situation is highly unsatisfactory. In fact, our research has led us to question the basic assumptions of conventional database indexing. We have spent the past ten years studying the properties of multi-dimensional indexing methods, and in this paper we draw the strands of a number of developments together - some quite old, some very new, to show how we now have the basis for a new generic indexing technology for the next generation of database systems.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients.

PubMed

Ma, Kevin C; Fernandez, James R; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S; Liu, Brent J

2015-12-01

MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. Copyright © 2015 Elsevier Ltd. All rights reserved.

Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients

PubMed Central

Ma, Kevin C.; Fernandez, James R.; Amezcua, Lilyana; Lerner, Alex; Shiroishi, Mark S.; Liu, Brent J.

2016-01-01

Purpose MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes. Method An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects. Summary The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record. PMID:26564667

CARES: Completely Automated Robust Edge Snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images: a two stage system combining an intensity-based feature approach with first order absolute moments

NASA Astrophysics Data System (ADS)

Molinari, Filippo; Acharya, Rajendra; Zeng, Guang; Suri, Jasjit S.

2011-03-01

The carotid intima-media thickness (IMT) is the most used marker for the progression of atherosclerosis and onset of the cardiovascular diseases. Computer-aided measurements improve accuracy, but usually require user interaction. In this paper we characterized a new and completely automated technique for carotid segmentation and IMT measurement based on the merits of two previously developed techniques. We used an integrated approach of intelligent image feature extraction and line fitting for automatically locating the carotid artery in the image frame, followed by wall interfaces extraction based on Gaussian edge operator. We called our system - CARES. We validated the CARES on a multi-institutional database of 300 carotid ultrasound images. IMT measurement bias was 0.032 +/- 0.141 mm, better than other automated techniques and comparable to that of user-driven methodologies. Our novel approach of CARES processed 96% of the images leading to the figure of merit to be 95.7%. CARES ensured complete automation and high accuracy in IMT measurement; hence it could be a suitable clinical tool for processing of large datasets in multicenter studies involving atherosclerosis.pre-

Possible costs associated with investigating and mitigating geologic hazards in rural areas of western San Mateo County, California with a section on using the USGS website to determine the cost of developing property for residences in rural parts of San Mateo County, California

USGS Publications Warehouse

Brabb, Earl E.; Roberts, Sebastian; Cotton, William R.; Kropp, Alan L.; Wright, Robert H.; Zinn, Erik N.; Digital database by Roberts, Sebastian; Mills, Suzanne K.; Barnes, Jason B.; Marsolek, Joanna E.

2000-01-01

This publication consists of a digital map database on a geohazards web site, http://kaibab.wr.usgs.gov/geohazweb/intro.htm, this text, and 43 digital map images available for downloading at this site. The report is stored as several digital files, in ARC export (uncompressed) format for the database, and Postscript and PDF formats for the map images. Several of the source data layers for the images have already been released in other publications by the USGS and are available for downloading on the Internet. These source layers are not included in this digital database, but rather a reference is given for the web site where the data can be found in digital format. The exported ARC coverages and grids lie in UTM zone 10 projection. The pamphlet, which only describes the content and character of the digital map database, is included as Postscript, PDF, and ASCII text files and is also available on paper as USGS Open-File Report 00-127. The full versatility of the spatial database is realized by importing the ARC export files into ARC/INFO or an equivalent GIS. Other GIS packages, including MapInfo and ARCVIEW, can also use the ARC export files. The Postscript map image can be used for viewing or plotting in computer systems with sufficient capacity, and the considerably smaller PDF image files can be viewed or plotted in full or in part from Adobe ACROBAT software running on Macintosh, PC, or UNIX platforms.

Ultrafast fingerprint indexing for embedded systems

NASA Astrophysics Data System (ADS)

Zhou, Ru; Sin, Sang Woo; Li, Dongju; Isshiki, Tsuyoshi; Kunieda, Hiroaki

2011-10-01

A novel core-based fingerprint indexing scheme for embedded systems is presented in this paper. Our approach is enabled by our new precise and fast core-detection algorithm with the direction map. It introduces the feature of CMP (core minutiae pair), which describes the coordinates of minutiae and the direction of ridges associated with the minutiae based on the uniquely defined core coordinates. Since each CMP is identical against the shift and rotation of the fingerprint image, the CMP comparison between a template and an input image can be performed without any alignment. The proposed indexing algorithm based on CMP is suitable for embedded systems because the tremendous speed up and the memory reduction are achieved. In fact, the experiments with the fingerprint database FVC2002 show that its speed for the identifications becomes about 40 times faster than conventional approaches, even though the database includes fingerprints with no core.

DR HAGIS-a fundus image database for the automatic extraction of retinal surface vessels from diabetic patients.

PubMed

Holm, Sven; Russell, Greg; Nourrit, Vincent; McLoughlin, Niall

2017-01-01

A database of retinal fundus images, the DR HAGIS database, is presented. This database consists of 39 high-resolution color fundus images obtained from a diabetic retinopathy screening program in the UK. The NHS screening program uses service providers that employ different fundus and digital cameras. This results in a range of different image sizes and resolutions. Furthermore, patients enrolled in such programs often display other comorbidities in addition to diabetes. Therefore, in an effort to replicate the normal range of images examined by grading experts during screening, the DR HAGIS database consists of images of varying image sizes and resolutions and four comorbidity subgroups: collectively defined as the diabetic retinopathy, hypertension, age-related macular degeneration, and Glaucoma image set (DR HAGIS). For each image, the vasculature has been manually segmented to provide a realistic set of images on which to test automatic vessel extraction algorithms. Modified versions of two previously published vessel extraction algorithms were applied to this database to provide some baseline measurements. A method based purely on the intensity of images pixels resulted in a mean segmentation accuracy of 95.83% ([Formula: see text]), whereas an algorithm based on Gabor filters generated an accuracy of 95.71% ([Formula: see text]).

Content Based Image Matching for Planetary Science

NASA Astrophysics Data System (ADS)

Deans, M. C.; Meyer, C.

2006-12-01

Planetary missions generate large volumes of data. With the MER rovers still functioning on Mars, PDS contains over 7200 released images from the Microscopic Imagers alone. These data products are only searchable by keys such as the Sol, spacecraft clock, or rover motion counter index, with little connection to the semantic content of the images. We have developed a method for matching images based on the visual textures in images. For every image in a database, a series of filters compute the image response to localized frequencies and orientations. Filter responses are turned into a low dimensional descriptor vector, generating a 37 dimensional fingerprint. For images such as the MER MI, this represents a compression ratio of 99.9965% (the fingerprint is approximately 0.0035% the size of the original image). At query time, fingerprints are quickly matched to find images with similar appearance. Image databases containing several thousand images are preprocessed offline in a matter of hours. Image matches from the database are found in a matter of seconds. We have demonstrated this image matching technique using three sources of data. The first database consists of 7200 images from the MER Microscopic Imager. The second database consists of 3500 images from the Narrow Angle Mars Orbital Camera (MOC-NA), which were cropped into 1024×1024 sub-images for consistency. The third database consists of 7500 scanned archival photos from the Apollo Metric Camera. Example query results from all three data sources are shown. We have also carried out user tests to evaluate matching performance by hand labeling results. User tests verify approximately 20% false positive rate for the top 14 results for MOC NA and MER MI data. This means typically 10 to 12 results out of 14 match the query image sufficiently. This represents a powerful search tool for databases of thousands of images where the a priori match probability for an image might be less than 1%. Qualitatively, correct matches can also be confirmed by verifying MI images taken in the same z-stack, or MOC image tiles taken from the same image strip. False negatives are difficult to quantify as it would mean finding matches in the database of thousands of images that the algorithm did not detect.

Computer systems for annotation of single molecule fragments

DOEpatents

Schwartz, David Charles; Severin, Jessica

2016-07-19

There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

Vessel extraction in retinal images using automatic thresholding and Gabor Wavelet.

PubMed

Ali, Aziah; Hussain, Aini; Wan Zaki, Wan Mimi Diyana

2017-07-01

Retinal image analysis has been widely used for early detection and diagnosis of multiple systemic diseases. Accurate vessel extraction in retinal image is a crucial step towards a fully automated diagnosis system. This work affords an efficient unsupervised method for extracting blood vessels from retinal images by combining existing Gabor Wavelet (GW) method with automatic thresholding. Green channel image is extracted from color retinal image and used to produce Gabor feature image using GW. Both green channel image and Gabor feature image undergo vessel-enhancement step in order to highlight blood vessels. Next, the two vessel-enhanced images are transformed to binary images using automatic thresholding before combined to produce the final vessel output. Combining the images results in significant improvement of blood vessel extraction performance compared to using individual image. Effectiveness of the proposed method was proven via comparative analysis with existing methods validated using publicly available database, DRIVE.

Multimedia systems for art and culture: a case study of Brihadisvara Temple

NASA Astrophysics Data System (ADS)

Jain, Anil K.; Goel, Sanjay; Agarwal, Sachin; Mittal, Vipin; Sharma, Hariom; Mahindru, Ranjeev

1997-01-01

In India a temple is not only a structure of religious significance and celebration, but it also plays an important role in the social, administrative and cultural life of the locality. Temples have served as centers for learning Indian scriptures. Music and dance were fostered and performed in the precincts of the temples. Built at the end of the 10th century, the Brihadisvara temple signified new design methodologies. We have access to a large number of images, audio and video recordings, architectural drawings and scholarly publications of this temple. A multimedia system for this temple is being designed which is intended to be used for the following purposes: (1) to inform and enrich the general public, and (2) to assist the scholars in their research. Such a system will also preserve and archive old historical documents and images. The large database consists primarily of images which can be retrieved using keywords, but the emphasis here is largely on techniques which will allow access using image content. Besides classifying images as either long shots or close-ups, deformable template matching is used for shape-based query by image content, and digital video retrieval. Further, to exploit the non-linear accessibility of video sequences, key frames are determined to aid the domain experts in getting a quick preview of the video. Our database also has images of several old, and rare manuscripts many of which are noisy and difficult to read. We have enhanced them to make them more legible. We are also investigating the optimal trade-off between image quality and compression ratios.

Utilization of a multimedia PACS workstation for surgical planning of epilepsy

NASA Astrophysics Data System (ADS)

Soo Hoo, Kent; Wong, Stephen T.; Hawkins, Randall A.; Knowlton, Robert C.; Laxer, Kenneth D.; Rowley, Howard A.

1997-05-01

Surgical treatment of temporal lobe epilepsy requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography, various neuroimaging modalities, and psychological tests together to determine the location of this zone. We investigate how a multimedia neuroimaging workstation built on top of the UCSF Picture Archiving and Communication System can be used to aid surgical planning of epilepsy and related brain diseases. This usage demonstrates the ability of the workstation to retrieve image and textural data from PACS and other image sources, register multimodality images, visualize and render 3D data sets, analyze images, generate new image and text data from the analysis, and organize all data in a relational database management system.

[Applications and advantages of a multimedia system for autopsies ].

PubMed

Gualco, M; Benzi, D; Fulcheri, E

2001-10-01

This work evaluates the benefits and applications of computers and multimedia systems in post-mortem examination practice and, more in particular, in the definition of data collection protocols. We examined issues concerning the different aims of autopsy (e.g. diagnostic, scientific, educational, legal), and found that the pathologist's main duty is to acquire a large amount of data in the best possible way. However, despite the will to carry out detailed post-mortem examinations, many pathologic anatomy services face objective difficulties in doing so, especially due to understaffing, lack of time and high costs. The Institute for Pathologic Anatomy of the University of Genoa has developed software for data handling and for outcome reporting, a particularly important aspect in fetal-perinatal diagnosis. The system consists of a relational database in a client-server environment (Fourth Dimension) with two integrated parts. The first part, with unrestricted access, contains patients' personal data, including gender, age, time and date of death, hospital department of origin, person and department requiring the post-mortem examination, hour and time of autopsy, pathologist's name, and clinical diagnosis of death. Using a scanner, a copy of the autopsy application is also field, together with the patient's medical file and any diagnostic images useful to document the case history. The second part of the information system is accessible by pathologists only, and contains the autopsy report. This part is organized to balance two different needs: it allows sufficient space and freedom for autopsy description while providing guidelines for presentation of the report. The structure of the conventional autopsy protocol has been maintained, with subdivisions for all the organs and apparatuses according to topographic criteria. Before this part, a section is dedicated to external cadaver examination and anthropometric data; weight, shape, volume and texture are described for each organ, together with external and cut-surface features. A third section allows the examiner to report other observations not requested previously, while a final section is also provided for the epicrisis and for the formulation of the final diagnosis, the same as that reported in the first form. The database is coupled with an interactive system for collecting voice comments, thereby replacing the need for tape-recorders in the autopsy room. The user can recall a dictation window, dictate a text, check spelling and insert additional text. The database is also coupled to an image acquisition system, on the assumption that moving images allow a more faithful documentation of reality. Therefore, all rooms in which autopsies are carried out on fetuses or neonates have been equipped with a fixed camera linked to a monitor and a video-recorder. A PCB, used for image digitalization, recognizes up to 16,000,000 different colors. Guided by dedicated software, image files are transferred to a computer and then saved with the autoptic report. The database can be consulted and queried in two principle ways: by key words in the contents or main disease descriptions, or by individual words or phrases contained within the complete text of the reports. The present database system for autopsy reporting has proved itself useful in a pathological anatomy service. The combined presence of images and texts renders the system useful also as a research tool. By linking to a Web site dedicated to pathologic anatomy, it will be possible to display online rare cases involving diagnostic difficulties. The system offers great advantages for present and retrospective diagnostics, as well as for research and education purposes.

Usefulness of Canadian Public Health Insurance Administrative Databases to Assess Breast and Ovarian Cancer Screening Imaging Technologies for BRCA1/2 Mutation Carriers.

PubMed

Larouche, Geneviève; Chiquette, Jocelyne; Plante, Marie; Pelletier, Sylvie; Simard, Jacques; Dorval, Michel

2016-11-01

In Canada, recommendations for clinical management of hereditary breast and ovarian cancer among individuals carrying a deleterious BRCA1 or BRCA2 mutation have been available since 2007. Eight years later, very little is known about the uptake of screening and risk-reduction measures in this population. Because Canada's public health care system falls under provincial jurisdictions, using provincial health care administrative databases appears a valuable option to assess management of BRCA1/2 mutation carriers. The objective was to explore the usefulness of public health insurance administrative databases in British Columbia, Ontario, and Quebec to assess management after BRCA1/2 genetic testing. Official public health insurance documents were considered potentially useful if they had specific procedure codes, and pertained to procedures performed in the public and private health care systems. All 3 administrative databases have specific procedures codes for mammography and breast ultrasounds. Only Quebec and Ontario have a specific procedure code for breast magnetic resonance imaging. It is impossible to assess, on an individual basis, the frequency of others screening exams, with the exception of CA-125 testing in British Columbia. Screenings done in private practice are excluded from the administrative databases unless covered by special agreements for reimbursement, such as all breast imaging exams in Ontario and mammograms in British Columbia and Quebec. There are no specific procedure codes for risk-reduction surgeries for breast and ovarian cancer. Population-based assessment of breast and ovarian cancer risk management strategies other than mammographic screening, using only administrative data, is currently challenging in the 3 Canadian provinces studied. Copyright © 2016 Canadian Association of Radiologists. Published by Elsevier Inc. All rights reserved.

Infrared Imaging System for Studying Brain Function

NASA Technical Reports Server (NTRS)

Mintz, Frederick; Mintz, Frederick; Gunapala, Sarath

2007-01-01

A proposed special-purpose infrared imaging system would be a compact, portable, less-expensive alternative to functional magnetic resonance imaging (fMRI) systems heretofore used to study brain function. Whereas a typical fMRI system fills a large room, and must be magnetically isolated, this system would fit into a bicycle helmet. The system would include an assembly that would be mounted inside the padding in a modified bicycle helmet or other suitable headgear. The assembly would include newly designed infrared photodetectors and data-acquisition circuits on integrated-circuit chips on low-thermal-conductivity supports in evacuated housings (see figure) arranged in multiple rows and columns that would define image coordinates. Each housing would be spring-loaded against the wearer s head. The chips would be cooled by a small Stirling Engine mounted contiguous to, but thermally isolated from, the portions of the assembly in thermal contact with the wearer s head. Flexible wires or cables for transmitting data from the aforementioned chips would be routed to an integrated, multichannel transmitter and thence through the top of the assembly to a patch antenna on the outside of the helmet. The multiple streams of data from the infrared-detector chips would be sent to a remote site, where they would be processed, by software, into a three-dimensional display of evoked potentials that would represent firing neuronal bundles and thereby indicate locations of neuronal activity associated with mental or physical activity. The 3D images will be analogous to current fMRI images. The data would also be made available, in real-time, for comparison with data in local or internationally accessible relational databases that already exist in universities and research centers. Hence, this system could be used in research on, and for the diagnosis of response from the wearer s brain to physiological, psychological, and environmental changes in real time. The images would also be stored in a relational database for comparison with corresponding responses previously observed in other subjects.

[Utility of axial images in an early Alzheimer disease diagnosis support system (VSRAD)].

PubMed

Goto, Masami; Aoki, Shigeki; Abe, Osamu; Masumoto, Tomohiko; Watanabe, Yasushi; Satake, Yoshiroh; Nishida, Katsuji; Ino, Kenji; Yano, Keiichi; Iida, Kyohhito; Mima, Kazuo; Ohtomo, Kuni

2006-09-20

In recent years, voxel-based morphometry (VBM) has become a popular tool for the early diagnosis of Alzheimer disease. The Voxel-Based Specific Regional Analysis System for Alzheimer's Disease (VSRAD), a VBM system that uses MRI, has been reported to be clinically useful. The able-bodied person database (DB) of VSRAD, which employs sagittal plane imaging, is not suitable for analysis by axial plane imaging. However, axial plane imaging is useful for avoiding motion artifacts from the eyeball. Therefore, we created an able-bodied person DB by axial plane imaging and examined its utility. We also analyzed groups of able-bodied persons and persons with dementia by axial plane imaging and reviewed the validity. After using the DB of axial plane imaging, the Z-score of the intrahippocampal region improved by 8 in 13 instances. In all brains, the Z-score improved by 13 in all instances.

A maize database resource that captures tissue-specific and subcellular-localized gene expression, via fluorescent tags and confocal imaging (Maize Cell Genomics Database).

PubMed

Krishnakumar, Vivek; Choi, Yongwook; Beck, Erin; Wu, Qingyu; Luo, Anding; Sylvester, Anne; Jackson, David; Chan, Agnes P

2015-01-01

Maize is a global crop and a powerful system among grain crops for genetic and genomic studies. However, the development of novel biological tools and resources to aid in the functional identification of gene sequences is greatly needed. Towards this goal, we have developed a collection of maize marker lines for studying native gene expression in specific cell types and subcellular compartments using fluorescent proteins (FPs). To catalog FP expression, we have developed a public repository, the Maize Cell Genomics (MCG) Database, (http://maize.jcvi.org/cellgenomics), to organize a large data set of confocal images generated from the maize marker lines. To date, the collection represents major subcellular structures and also developmentally important progenitor cell populations. The resource is available to the research community, for example to study protein localization or interactions under various experimental conditions or mutant backgrounds. A subset of the marker lines can also be used to induce misexpression of target genes through a transactivation system. For future directions, the image repository can be expanded to accept new image submissions from the research community, and to perform customized large-scale computational image analysis. This community resource will provide a suite of new tools for gaining biological insights by following the dynamics of protein expression at the subcellular, cellular and tissue levels. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Faster, efficient and secure collection of research images: the utilization of cloud technology to expand the OMI-DB

NASA Astrophysics Data System (ADS)

Patel, M. N.; Young, K.; Halling-Brown, M. D.

2018-03-01

The demand for medical images for research is ever increasing owing to the rapid rise in novel machine learning approaches for early detection and diagnosis. The OPTIMAM Medical Image Database (OMI-DB)1,2 was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, annotations and expert-determined ground truths. Since the inception of the database in early 2011, the volume of images and associated data collected has dramatically increased owing to automation of the collection pipeline and inclusion of new sites. Currently, these data are stored at each respective collection site and synced periodically to a central store. This leads to a large data footprint at each site, requiring large physical onsite storage, which is expensive. Here, we propose an update to the OMI-DB collection system, whereby the storage of all the data is automatically transferred to the cloud on collection. This change in the data collection paradigm reduces the reliance of physical servers at each site; allows greater scope for future expansion; and removes the need for dedicated backups and improves security. Moreover, with the number of applications to access the data increasing rapidly with the maturity of the dataset cloud technology facilities faster sharing of data and better auditing of data access. Such updates, although may sound trivial; require substantial modification to the existing pipeline to ensure data integrity and security compliance. Here, we describe the extensions to the OMI-DB collection pipeline and discuss the relative merits of the new system.

Wheat gliadin: digital imaging and database construction using a 4-band reference system of agarose isoelectric focusing patterns.

PubMed

Black, J A; Waggamon, K A

1992-01-01

An isoelectric focusing method using thin-layer agarose gel has been developed for wheat gliadin. Using flat-bed units with a third electrode, up to 72 samples per gel may be analyzed. Advantages over traditional acid polyacrylamide gel electrophoresis methodology include: faster run times, nontoxic media, and greater sample capacity. The method is suitable for fingerprinting or purity testing of wheat varieties. Using digital images captured by a flat-bed scanner, a 4-band reference system using isoelectric points was devised. Software enables separated bands to be assigned pI values based upon reference tracks. Precision of assigned isoelectric points is shown to be on the order of 0.02 pH units. Captured images may be stored in a computer database and compared to unknown patterns to enable an identification. Parameters for a match with a stored pattern may be adjusted for pI interval required for a match, and number of best matches.

Shift-invariant discrete wavelet transform analysis for retinal image classification.

PubMed

Khademi, April; Krishnan, Sridhar

2007-12-01

This work involves retinal image classification and a novel analysis system was developed. From the compressed domain, the proposed scheme extracts textural features from wavelet coefficients, which describe the relative homogeneity of localized areas of the retinal images. Since the discrete wavelet transform (DWT) is shift-variant, a shift-invariant DWT was explored to ensure that a robust feature set was extracted. To combat the small database size, linear discriminant analysis classification was used with the leave one out method. 38 normal and 48 abnormal (exudates, large drusens, fine drusens, choroidal neovascularization, central vein and artery occlusion, histoplasmosis, arteriosclerotic retinopathy, hemi-central retinal vein occlusion and more) were used and a specificity of 79% and sensitivity of 85.4% were achieved (the average classification rate is 82.2%). The success of the system can be accounted to the highly robust feature set which included translation, scale and semi-rotational, features. Additionally, this technique is database independent since the features were specifically tuned to the pathologies of the human eye.

Computer-Assisted Promotion of Recreational Opportunities in Natural Resource Areas: A Demonstration and Case Example

Treesearch

Emilyn Sheffield; Leslie Furr; Charles Nelson

1992-01-01

Filevision IV is a multilayer imaging and data-base management system that combines drawing, filing and extensive report-writing capabilities (Filevision IV, 1988). Filevision IV users access data by attaching graphics to text-oriented data-base records. Tourist attractions, support services, and geo-graphic features can be located on a base map of an area or region....

Database for the collection and analysis of clinical data and images of neoplasms of the sinonasal tract.

PubMed

Trimarchi, Matteo; Lund, Valerie J; Nicolai, Piero; Pini, Massimiliano; Senna, Massimo; Howard, David J

2004-04-01

The Neoplasms of the Sinonasal Tract software package (NSNT v 1.0) implements a complete visual database for patients with sinonasal neoplasia, facilitating standardization of data and statistical analysis. The software, which is compatible with the Macintosh and Windows platforms, provides multiuser application with a dedicated server (on Windows NT or 2000 or Macintosh OS 9 or X and a network of clients) together with web access, if required. The system hardware consists of an Apple Power Macintosh G4500 MHz computer with PCI bus, 256 Mb of RAM plus 60 Gb hard disk, or any IBM-compatible computer with a Pentium 2 processor. Image acquisition may be performed with different frame-grabber cards for analog or digital video input of different standards (PAL, SECAM, or NTSC) and levels of quality (VHS, S-VHS, Betacam, Mini DV, DV). The visual database is based on 4th Dimension by 4D Inc, and video compression is made in real-time MPEG format. Six sections have been developed: demographics, symptoms, extent of disease, radiology, treatment, and follow-up. Acquisition of data includes computed tomography and magnetic resonance imaging, histology, and endoscopy images, allowing sequential comparison. Statistical analysis integral to the program provides Kaplan-Meier survival curves. The development of a dedicated, user-friendly database for sinonasal neoplasia facilitates a multicenter network and has obvious clinical and research benefits.

Seeing is believing: on the use of image databases for visually exploring plant organelle dynamics.

PubMed

Mano, Shoji; Miwa, Tomoki; Nishikawa, Shuh-ichi; Mimura, Tetsuro; Nishimura, Mikio

2009-12-01

Organelle dynamics vary dramatically depending on cell type, developmental stage and environmental stimuli, so that various parameters, such as size, number and behavior, are required for the description of the dynamics of each organelle. Imaging techniques are superior to other techniques for describing organelle dynamics because these parameters are visually exhibited. Therefore, as the results can be seen immediately, investigators can more easily grasp organelle dynamics. At present, imaging techniques are emerging as fundamental tools in plant organelle research, and the development of new methodologies to visualize organelles and the improvement of analytical tools and equipment have allowed the large-scale generation of image and movie data. Accordingly, image databases that accumulate information on organelle dynamics are an increasingly indispensable part of modern plant organelle research. In addition, image databases are potentially rich data sources for computational analyses, as image and movie data reposited in the databases contain valuable and significant information, such as size, number, length and velocity. Computational analytical tools support image-based data mining, such as segmentation, quantification and statistical analyses, to extract biologically meaningful information from each database and combine them to construct models. In this review, we outline the image databases that are dedicated to plant organelle research and present their potential as resources for image-based computational analyses.

Passive millimeter wave simulation in blender

NASA Astrophysics Data System (ADS)

Murakowski, Maciej

Imaging in the millimeter wave (mmW) frequency range is being explored for applications where visible or infrared (IR) imaging fails, such as through atmospheric obscurants. However, mmW imaging is still in its infancy and imager systems are still bulky, expensive, and fragile, so experiments on imaging in real-world scenarios are difficult or impossible to perform. Therefore, a simulation system capable of predicting mmW phenomenology would be valuable in determining the requirements (e.g. resolution or noise floor) of an imaging system for a particular scenario and aid in the design of such an imager. Producing simulation software for this purpose is the objective of the work described in this thesis. The 3D software package Blender was modified to simulate the images produced by a passive mmW imager, based on a Geometrical Optics approach. Simulated imagery was validated against experimental data and the software was applied to novel imaging scenarios. Additionally, a database of material properties for use in the simulation was collected.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Comparison of photo-matching algorithms commonly used for photographic capture-recapture studies.

PubMed

Matthé, Maximilian; Sannolo, Marco; Winiarski, Kristopher; Spitzen-van der Sluijs, Annemarieke; Goedbloed, Daniel; Steinfartz, Sebastian; Stachow, Ulrich

2017-08-01

Photographic capture-recapture is a valuable tool for obtaining demographic information on wildlife populations due to its noninvasive nature and cost-effectiveness. Recently, several computer-aided photo-matching algorithms have been developed to more efficiently match images of unique individuals in databases with thousands of images. However, the identification accuracy of these algorithms can severely bias estimates of vital rates and population size. Therefore, it is important to understand the performance and limitations of state-of-the-art photo-matching algorithms prior to implementation in capture-recapture studies involving possibly thousands of images. Here, we compared the performance of four photo-matching algorithms; Wild-ID, I3S Pattern+, APHIS, and AmphIdent using multiple amphibian databases of varying image quality. We measured the performance of each algorithm and evaluated the performance in relation to database size and the number of matching images in the database. We found that algorithm performance differed greatly by algorithm and image database, with recognition rates ranging from 100% to 22.6% when limiting the review to the 10 highest ranking images. We found that recognition rate degraded marginally with increased database size and could be improved considerably with a higher number of matching images in the database. In our study, the pixel-based algorithm of AmphIdent exhibited superior recognition rates compared to the other approaches. We recommend carefully evaluating algorithm performance prior to using it to match a complete database. By choosing a suitable matching algorithm, databases of sizes that are unfeasible to match "by eye" can be easily translated to accurate individual capture histories necessary for robust demographic estimates.

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

Cenozoic Antarctic DiatomWare/BugCam: An aid for research and teaching

USGS Publications Warehouse

Wise, S.W.; Olney, M.; Covington, J.M.; Egerton, V.M.; Jiang, S.; Ramdeen, D.K.; ,; Schrader, H.; Sims, P.A.; Wood, A.S.; Davis, A.; Davenport, D.R.; Doepler, N.; Falcon, W.; Lopez, C.; Pressley, T.; Swedberg, O.L.; Harwood, D.M.

2007-01-01

Cenozoic Antarctic DiatomWare/BugCam© is an interactive, icon-driven digital-image database/software package that displays over 500 illustrated Cenozoic Antarctic diatom taxa along with original descriptions (including over 100 generic and 20 family-group descriptions). This digital catalog is designed primarily for use by micropaleontologists working in the field (at sea or on the Antarctic continent) where hard-copy literature resources are limited. This new package will also be useful for classroom/lab teaching as well as for any paleontologists making or refining taxonomic identifications at the microscope. The database (Cenozoic Antarctic DiatomWare) is displayed via a custom software program (BugCam) written in Visual Basic for use on PCs running Windows 95 or later operating systems. BugCam is a flexible image display program that utilizes an intuitive thumbnail “tree” structure for navigation through the database. The data are stored on Micrsosoft EXCEL spread sheets, hence no separate relational database program is necessary to run the package

Face detection on distorted images using perceptual quality-aware features

NASA Astrophysics Data System (ADS)

Gunasekar, Suriya; Ghosh, Joydeep; Bovik, Alan C.

2014-02-01

We quantify the degradation in performance of a popular and effective face detector when human-perceived image quality is degraded by distortions due to additive white gaussian noise, gaussian blur or JPEG compression. It is observed that, within a certain range of perceived image quality, a modest increase in image quality can drastically improve face detection performance. These results can be used to guide resource or bandwidth allocation in a communication/delivery system that is associated with face detection tasks. A new face detector based on QualHOG features is also proposed that augments face-indicative HOG features with perceptual quality-aware spatial Natural Scene Statistics (NSS) features, yielding improved tolerance against image distortions. The new detector provides statistically significant improvements over a strong baseline on a large database of face images representing a wide range of distortions. To facilitate this study, we created a new Distorted Face Database, containing face and non-face patches from images impaired by a variety of common distortion types and levels. This new dataset is available for download and further experimentation at www.ideal.ece.utexas.edu/˜suriya/DFD/.

Reference point detection for camera-based fingerprint image based on wavelet transformation.

PubMed

Khalil, Mohammed S

2015-04-30

Fingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone. The proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method's output with the defined core points. The proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%. The proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.

Clinical experience with PACS at Northwestern: year two

NASA Astrophysics Data System (ADS)

Channin, David S.; Hawkins, Rodney C.; Enzmann, Dieter R.

2001-08-01

We have previously described the PACS configuration at Northwestern Memorial Hospital (NMH). As opposed to an imaging modality, PACS is an evolving system that continuously grows and changes to meet the needs of the institution. The NMH PACS has grown significantly in the past year and has undergone significant architectural enhancements. This growth and evolutionary change will be described and discussed. The system now contains over 339,000 studies consisting of over 13 million images. There are now two short-term RAID storage units that provide for twice as much fast storage. There are also two magneto-optical disk jukeboxes providing long-term archive. We have deployed a redundant database to improve reliability of the system in the event of database failure. The number of modalities connected to the system has increased and will be summarized. Statistics describing utilization of the PACS will be shown. Lastly, we will discuss our plans for exploiting the application service provider model in our PACS environment.

Boost OCR accuracy using iVector based system combination approach

NASA Astrophysics Data System (ADS)

Peng, Xujun; Cao, Huaigu; Natarajan, Prem

2015-01-01

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

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

The Alaska Volcano Observatory Website a Tool for Information Management and Dissemination

NASA Astrophysics Data System (ADS)

Snedigar, S. F.; Cameron, C. E.; Nye, C. J.

2006-12-01

The Alaska Volcano Observatory's (AVO's) website served as a primary information management tool during the 2006 eruption of Augustine Volcano. The AVO website is dynamically generated from a database back- end. This system enabled AVO to quickly and easily update the website, and provide content based on user- queries to the database. During the Augustine eruption, the new AVO website was heavily used by members of the public (up to 19 million hits per day), and this was largely because the AVO public pages were an excellent source of up-to-date information. There are two different, yet fully integrated parts of the website. An external, public site (www.avo.alaska.edu) allows the general public to track eruptive activity by viewing the latest photographs, webcam images, webicorder graphs, and official information releases about activity at the volcano, as well as maps, previous eruption information, bibliographies, and rich information about other Alaska volcanoes. The internal half of the website hosts diverse geophysical and geological data (as browse images) in a format equally accessible by AVO staff in different locations. In addition, an observation log allows users to enter information about anything from satellite passes to seismic activity to ash fall reports into a searchable database. The individual(s) on duty at the watch office use forms on the internal website to post a summary of the latest activity directly to the public website, ensuring that the public website is always up to date. The internal website also serves as a starting point for monitoring Alaska's volcanoes. AVO's extensive image database allows AVO personnel to upload many photos, diagrams, and videos which are then available to be browsed by anyone in the AVO community. Selected images are viewable from the public page. The primary webserver is housed at the University of Alaska Fairbanks, and holds a MySQL database with over 200 tables and several thousand lines of php code gluing the database and website together. The database currently holds 95 GB of data. Webcam images and webicorder graphs are pulled from servers in Anchorage every few minutes. Other servers in Fairbanks generate earthquake location plots and spectrograms.

The Brain Database: A Multimedia Neuroscience Database for Research and Teaching

PubMed Central

Wertheim, Steven L.

1989-01-01

The Brain Database is an information tool designed to aid in the integration of clinical and research results in neuroanatomy and regional biochemistry. It can handle a wide range of data types including natural images, 2 and 3-dimensional graphics, video, numeric data and text. It is organized around three main entities: structures, substances and processes. The database will support a wide variety of graphical interfaces. Two sample interfaces have been made. This tool is intended to serve as one component of a system that would allow neuroscientists and clinicians 1) to represent clinical and experimental data within a common framework 2) to compare results precisely between experiments and among laboratories, 3) to use computing tools as an aid in collaborative work and 4) to contribute to a shared and accessible body of knowledge about the nervous system.

Spotting words in handwritten Arabic documents

NASA Astrophysics Data System (ADS)

Srihari, Sargur; Srinivasan, Harish; Babu, Pavithra; Bhole, Chetan

2006-01-01

The design and performance of a system for spotting handwritten Arabic words in scanned document images is presented. Three main components of the system are a word segmenter, a shape based matcher for words and a search interface. The user types in a query in English within a search window, the system finds the equivalent Arabic word, e.g., by dictionary look-up, locates word images in an indexed (segmented) set of documents. A two-step approach is employed in performing the search: (1) prototype selection: the query is used to obtain a set of handwritten samples of that word from a known set of writers (these are the prototypes), and (2) word matching: the prototypes are used to spot each occurrence of those words in the indexed document database. A ranking is performed on the entire set of test word images-- where the ranking criterion is a similarity score between each prototype word and the candidate words based on global word shape features. A database of 20,000 word images contained in 100 scanned handwritten Arabic documents written by 10 different writers was used to study retrieval performance. Using five writers for providing prototypes and the other five for testing, using manually segmented documents, 55% precision is obtained at 50% recall. Performance increases as more writers are used for training.

Implementation of Automatic Focusing Algorithms for a Computer Vision System with Camera Control.

DTIC Science & Technology

1983-08-15

obtainable from real data, rather than relying on a stock database. Often, computer vision and image processing algorithms become subconsciously tuned to...two coils on the same mount structure. Since it was not possible to reprogram the binary system, we turned to the POPEYE system for both its grey

Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program

DTIC Science & Technology

1991-10-01

Knowledge System The CKS is an object-oriented knowledge database that was originally designed to serve as the central information manager for a...34 Representation Space: An Approach to the Integra- tion of Visual Information ," Proc. of DARPA Image Understanding Workshop, Palo Alto, CA, pp. 263-272, May 1989...Strat, " Information Management in a Sensor-Based Au- tonomous System," Proc. DARPA Image Understanding Workshop, University of Southern CA, Vol.1, pp

Development and Demonstration of a Networked Telepathology 3-D Imaging, Databasing, and Communication System

DTIC Science & Technology

1996-10-01

aligned using an octree search algorithm combined with cross correlation analysis . Successive 4x downsampling with optional and specifiable neighborhood...desired and the search engine embedded in the OODBMS will find the requested imagery and que it to the user for further analysis . This application was...obtained during Hoftmann-LaRoche production pathology imaging performed at UMICH. Versant works well and is easy to use; 3) Pathology Image Analysis

Integrated radiologist's workstation enabling the radiologist as an effective clinical consultant

NASA Astrophysics Data System (ADS)

McEnery, Kevin W.; Suitor, Charles T.; Hildebrand, Stan; Downs, Rebecca; Thompson, Stephen K.; Shepard, S. Jeff

2002-05-01

Since February 2000, radiologists at the M. D. Anderson Cancer Center have accessed clinical information through an internally developed radiologist's clinical interpretation workstation called RadStation. This project provides a fully integrated digital dictation workstation with clinical data review. RadStation enables the radiologist as an effective clinical consultant with access to pertinent sources of clinical information at the time of dictation. Data sources not only include prior radiology reports from the radiology information system (RIS) but access to pathology data, laboratory data, history and physicals, clinic notes, and operative reports. With integrated clinical information access, a radiologists's interpretation not only comments on morphologic findings but also can enable evaluation of study findings in the context of pertinent clinical presentation and history. Image access is enabled through the integration of an enterprise image archive (Stentor, San Francisco). Database integration is achieved by a combination of real time HL7 messaging and queries to SQL-based legacy databases. A three-tier system architecture accommodates expanding access to additional databases including real-time patient schedule as well as patient medications and allergies.

NVST Data Archiving System Based On FastBit NoSQL Database

NASA Astrophysics Data System (ADS)

Liu, Ying-bo; Wang, Feng; Ji, Kai-fan; Deng, Hui; Dai, Wei; Liang, Bo

2014-06-01

The New Vacuum Solar Telescope (NVST) is a 1-meter vacuum solar telescope that aims to observe the fine structures of active regions on the Sun. The main tasks of the NVST are high resolution imaging and spectral observations, including the measurements of the solar magnetic field. The NVST has been collecting more than 20 million FITS files since it began routine observations in 2012 and produces a maximum observational records of 120 thousand files in a day. Given the large amount of files, the effective archiving and retrieval of files becomes a critical and urgent problem. In this study, we implement a new data archiving system for the NVST based on the Fastbit Not Only Structured Query Language (NoSQL) database. Comparing to the relational database (i.e., MySQL; My Structured Query Language), the Fastbit database manifests distinctive advantages on indexing and querying performance. In a large scale database of 40 million records, the multi-field combined query response time of Fastbit database is about 15 times faster and fully meets the requirements of the NVST. Our study brings a new idea for massive astronomical data archiving and would contribute to the design of data management systems for other astronomical telescopes.

Handwritten word preprocessing for database adaptation

NASA Astrophysics Data System (ADS)

Oprean, Cristina; Likforman-Sulem, Laurence; Mokbel, Chafic

2013-01-01

Handwriting recognition systems are typically trained using publicly available databases, where data have been collected in controlled conditions (image resolution, paper background, noise level,...). Since this is not often the case in real-world scenarios, classification performance can be affected when novel data is presented to the word recognition system. To overcome this problem, we present in this paper a new approach called database adaptation. It consists of processing one set (training or test) in order to adapt it to the other set (test or training, respectively). Specifically, two kinds of preprocessing, namely stroke thickness normalization and pixel intensity normalization are considered. The advantage of such approach is that we can re-use the existing recognition system trained on controlled data. We conduct several experiments with the Rimes 2011 word database and with a real-world database. We adapt either the test set or the training set. Results show that training set adaptation achieves better results than test set adaptation, at the cost of a second training stage on the adapted data. Accuracy of data set adaptation is increased by 2% to 3% in absolute value over no adaptation.

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.

Automated extraction of chemical structure information from digital raster images

PubMed Central

Park, Jungkap; Rosania, Gus R; Shedden, Kerby A; Nguyen, Mandee; Lyu, Naesung; Saitou, Kazuhiro

2009-01-01

Background To search for chemical structures in research articles, diagrams or text representing molecules need to be translated to a standard chemical file format compatible with cheminformatic search engines. Nevertheless, chemical information contained in research articles is often referenced as analog diagrams of chemical structures embedded in digital raster images. To automate analog-to-digital conversion of chemical structure diagrams in scientific research articles, several software systems have been developed. But their algorithmic performance and utility in cheminformatic research have not been investigated. Results This paper aims to provide critical reviews for these systems and also report our recent development of ChemReader – a fully automated tool for extracting chemical structure diagrams in research articles and converting them into standard, searchable chemical file formats. Basic algorithms for recognizing lines and letters representing bonds and atoms in chemical structure diagrams can be independently run in sequence from a graphical user interface-and the algorithm parameters can be readily changed-to facilitate additional development specifically tailored to a chemical database annotation scheme. Compared with existing software programs such as OSRA, Kekule, and CLiDE, our results indicate that ChemReader outperforms other software systems on several sets of sample images from diverse sources in terms of the rate of correct outputs and the accuracy on extracting molecular substructure patterns. Conclusion The availability of ChemReader as a cheminformatic tool for extracting chemical structure information from digital raster images allows research and development groups to enrich their chemical structure databases by annotating the entries with published research articles. Based on its stable performance and high accuracy, ChemReader may be sufficiently accurate for annotating the chemical database with links to scientific research articles. PMID:19196483

Differentiation of several interstitial lung disease patterns in HRCT images using support vector machine: role of databases on performance

NASA Astrophysics Data System (ADS)

Kale, Mandar; Mukhopadhyay, Sudipta; Dash, Jatindra K.; Garg, Mandeep; Khandelwal, Niranjan

2016-03-01

Interstitial lung disease (ILD) is complicated group of pulmonary disorders. High Resolution Computed Tomography (HRCT) considered to be best imaging technique for analysis of different pulmonary disorders. HRCT findings can be categorised in several patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Nodular, Normal etc. based on their texture like appearance. Clinician often find it difficult to diagnosis these pattern because of their complex nature. In such scenario computer-aided diagnosis system could help clinician to identify patterns. Several approaches had been proposed for classification of ILD patterns. This includes computation of textural feature and training /testing of classifier such as artificial neural network (ANN), support vector machine (SVM) etc. In this paper, wavelet features are calculated from two different ILD database, publically available MedGIFT ILD database and private ILD database, followed by performance evaluation of ANN and SVM classifiers in terms of average accuracy. It is found that average classification accuracy by SVM is greater than ANN where trained and tested on same database. Investigation continued further to test variation in accuracy of classifier when training and testing is performed with alternate database and training and testing of classifier with database formed by merging samples from same class from two individual databases. The average classification accuracy drops when two independent databases used for training and testing respectively. There is significant improvement in average accuracy when classifiers are trained and tested with merged database. It infers dependency of classification accuracy on training data. It is observed that SVM outperforms ANN when same database is used for training and testing.

Spectral imaging of neurosurgical target tissues through operation microscope

NASA Astrophysics Data System (ADS)

Antikainen, Jukka; von Und Zu Fraunberg, Mikael; Orava, Joni; Jaaskelainen, Juha E.; Hauta-Kasari, Markku

2011-11-01

It has been noticed that spectral information can be used for analyzing and separating different biological tissues. However, most of the studies for spectral image acquisitions are mainly done in vitro. Usually the main restrictions for in vivo measurements are the size or the weight of the spectral camera. If the camera weights too much, the surgery microscope cannot be stabilized. If the size of the camera is too big, it will disturb the surgeon or even risk the safety of the patient. The main goal of this study was to develop an independent spectral imaging device which can be used for collecting spectral information from the neurosurgeries without any previously described restrictions. Size of the imaging system is small enough not to disturb the surgeon during the surgery. The developed spectral imaging system is used for collecting a spectral database which can be used for the future imaging systems.

JPEG2000 and dissemination of cultural heritage over the Internet.

PubMed

Politou, Eugenia A; Pavlidis, George P; Chamzas, Christodoulos

2004-03-01

By applying the latest technologies in image compression for managing the storage of massive image data within cultural heritage databases and by exploiting the universality of the Internet we are now able not only to effectively digitize, record and preserve, but also to promote the dissemination of cultural heritage. In this work we present an application of the latest image compression standard JPEG2000 in managing and browsing image databases, focusing on the image transmission aspect rather than database management and indexing. We combine the technologies of JPEG2000 image compression with client-server socket connections and client browser plug-in, as to provide with an all-in-one package for remote browsing of JPEG2000 compressed image databases, suitable for the effective dissemination of cultural heritage.

Clinical results of HIS, RIS, PACS integration using data integration CASE tools

NASA Astrophysics Data System (ADS)

Taira, Ricky K.; Chan, Hing-Ming; Breant, Claudine M.; Huang, Lu J.; Valentino, Daniel J.

1995-05-01

Current infrastructure research in PACS is dominated by the development of communication networks (local area networks, teleradiology, ATM networks, etc.), multimedia display workstations, and hierarchical image storage architectures. However, limited work has been performed on developing flexible, expansible, and intelligent information processing architectures for the vast decentralized image and text data repositories prevalent in healthcare environments. Patient information is often distributed among multiple data management systems. Current large-scale efforts to integrate medical information and knowledge sources have been costly with limited retrieval functionality. Software integration strategies to unify distributed data and knowledge sources is still lacking commercially. Systems heterogeneity (i.e., differences in hardware platforms, communication protocols, database management software, nomenclature, etc.) is at the heart of the problem and is unlikely to be standardized in the near future. In this paper, we demonstrate the use of newly available CASE (computer- aided software engineering) tools to rapidly integrate HIS, RIS, and PACS information systems. The advantages of these tools include fast development time (low-level code is generated from graphical specifications), and easy system maintenance (excellent documentation, easy to perform changes, and centralized code repository in an object-oriented database). The CASE tools are used to develop and manage the `middle-ware' in our client- mediator-serve architecture for systems integration. Our architecture is scalable and can accommodate heterogeneous database and communication protocols.

Cross-Service Investigation of Geographical Information Systems

DTIC Science & Technology

2004-03-01

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

Optic disk localization by a robust fusion method

NASA Astrophysics Data System (ADS)

Zhang, Jielin; Yin, Fengshou; Wong, Damon W. K.; Liu, Jiang; Baskaran, Mani; Cheng, Ching-Yu; Wong, Tien Yin

2013-02-01

The optic disk localization plays an important role in developing computer-aided diagnosis (CAD) systems for ocular diseases such as glaucoma, diabetic retinopathy and age-related macula degeneration. In this paper, we propose an intelligent fusion of methods for the localization of the optic disk in retinal fundus images. Three different approaches are developed to detect the location of the optic disk separately. The first method is the maximum vessel crossing method, which finds the region with the most number of blood vessel crossing points. The second one is the multichannel thresholding method, targeting the area with the highest intensity. The final method searches the vertical and horizontal region-of-interest separately on the basis of blood vessel structure and neighborhood entropy profile. Finally, these three methods are combined using an intelligent fusion method to improve the overall accuracy. The proposed algorithm was tested on the STARE database and the ORIGAlight database, each consisting of images with various pathologies. The preliminary result on the STARE database can achieve 81.5%, while a higher result of 99% can be obtained for the ORIGAlight database. The proposed method outperforms each individual approach and state-of-the-art method which utilizes an intensity-based approach. The result demonstrates a high potential for this method to be used in retinal CAD systems.

A COSTAR interface using WWW technology.

PubMed Central

Rabbani, U.; Morgan, M.; Barnett, O.

1998-01-01

The concentration of industry on modern relational databases has left many nonrelational and proprietary databases without support for integration with new technologies. Emerging interface tools and data-access methodologies can be applied with difficulty to medical record systems which have proprietary data representation. Users of such medical record systems usually must access the clinical content of such record systems with keyboard-intensive and time-consuming interfaces. COSTAR is a legacy ambulatory medical record system developed over 25 years ago that is still popular and extensively used at the Massachusetts General Hospital. We define a model for using middle layer services to extract and cache data from non-relational databases, and present an intuitive World-Wide Web interface to COSTAR. This model has been implemented and successfully piloted in the Internal Medicine Associates at Massachusetts General Hospital. Images Figure 1 Figure 2 Figure 3 Figure 4 PMID:9929310

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).

Online molecular image repository and analysis system: A multicenter collaborative open-source infrastructure for molecular imaging research and application.

PubMed

Rahman, Mahabubur; Watabe, Hiroshi

2018-05-01

Molecular imaging serves as an important tool for researchers and clinicians to visualize and investigate complex biochemical phenomena using specialized instruments; these instruments are either used individually or in combination with targeted imaging agents to obtain images related to specific diseases with high sensitivity, specificity, and signal-to-noise ratios. However, molecular imaging, which is a multidisciplinary research field, faces several challenges, including the integration of imaging informatics with bioinformatics and medical informatics, requirement of reliable and robust image analysis algorithms, effective quality control of imaging facilities, and those related to individualized disease mapping, data sharing, software architecture, and knowledge management. As a cost-effective and open-source approach to address these challenges related to molecular imaging, we develop a flexible, transparent, and secure infrastructure, named MIRA, which stands for Molecular Imaging Repository and Analysis, primarily using the Python programming language, and a MySQL relational database system deployed on a Linux server. MIRA is designed with a centralized image archiving infrastructure and information database so that a multicenter collaborative informatics platform can be built. The capability of dealing with metadata, image file format normalization, and storing and viewing different types of documents and multimedia files make MIRA considerably flexible. With features like logging, auditing, commenting, sharing, and searching, MIRA is useful as an Electronic Laboratory Notebook for effective knowledge management. In addition, the centralized approach for MIRA facilitates on-the-fly access to all its features remotely through any web browser. Furthermore, the open-source approach provides the opportunity for sustainable continued development. MIRA offers an infrastructure that can be used as cross-boundary collaborative MI research platform for the rapid achievement in cancer diagnosis and therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

RIS integrated IMAC system

NASA Astrophysics Data System (ADS)

Angelhed, Jan-Erik; Carlsson, Goeran; Gustavsson, Staffan; Karlsson, Anders; Larsson, Lars E. G.; Svensson, Sune; Tylen, Ulf

1998-07-01

An Image Management And Communication (IMAC) system adapted to the X-ray department at Sahlgrenska University Hospital has been developed using standard components. Two user demands have been considered primary: Rapid access to (display of) images and an efficient worklist management. To fulfil these demands a connection between the IMAC system and the existing Radiological Information System (RIS) has been implemented. The functional modules are: check of information consistency in data exported from image sources, a (logically) central storage of image data, viewing facility for high speed-, large volume-, clinical work, and an efficient interface to the RIS. Also, an image related database extension has been made to the RIS. The IMAC system has a strictly modular design with a simple structure. The image archive and short term storage are logically the same and acts as a huge disk. Through NFS all image data is available to all the connected workstations. All patient selection for viewing is through worklists, which are created by selection criteria in the RIS, by the use of barcodes, or, in singular cases, by entering the patient ID by hand.

Designing a multi-petabyte database for LSST

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

Becla, J; Hanushevsky, A

2005-12-21

The 3.2 giga-pixel LSST camera will produce over half a petabyte of raw images every month. This data needs to be reduced in under a minute to produce real-time transient alerts, and then cataloged and indexed to allow efficient access and simplify further analysis. The indexed catalogs alone are expected to grow at a speed of about 600 terabytes per year. The sheer volume of data, the real-time transient alerting requirements of the LSST, and its spatio-temporal aspects require cutting-edge techniques to build an efficient data access system at reasonable cost. As currently envisioned, the system will rely on amore » database for catalogs and metadata. Several database systems are being evaluated to understand how they will scale and perform at these data volumes in anticipated LSST access patterns. This paper describes the LSST requirements, the challenges they impose, the data access philosophy, and the database architecture that is expected to be adopted in order to meet the data challenges.« less

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

PubMed

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines. We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to enable rapid diagnosis and for patient follow-up, with an execution time of only 6 seconds per image. Copyright © 2018 Elsevier B.V. All rights reserved.

A Knowledge-Based System for the Computer Assisted Diagnosis of Endoscopic Images

NASA Astrophysics Data System (ADS)

Kage, Andreas; Münzenmayer, Christian; Wittenberg, Thomas

Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively.

An Intelligent Pictorial Information System

NASA Astrophysics Data System (ADS)

Lee, Edward T.; Chang, B.

1987-05-01

In examining the history of computer application, we discover that early computer systems were developed primarily for applications related to scientific computation, as in weather prediction, aerospace applications, and nuclear physics applications. At this stage, the computer system served as a big calculator to perform, in the main, manipulation of numbers. Then it was found that computer systems could also be used for business applications, information storage and retrieval, word processing, and report generation. The history of computer application is summarized in Table I. The complexity of pictures makes picture processing much more difficult than number and alphanumerical processing. Therefore, new techniques, new algorithms, and above all, new pictorial knowledge, [1] are needed to overcome the limitatins of existing computer systems. New frontiers in designing computer systems are the ways to handle the representation,[2,3] classification, manipulation, processing, storage, and retrieval of pictures. Especially, the ways to deal with similarity measures and the meaning of the word "approximate" and the phrase "approximate reasoning" are an important and an indispensable part of an intelligent pictorial information system. [4,5] The main objective of this paper is to investigate the mathematical foundation for the effective organization and efficient retrieval of pictures in similarity-directed pictorial databases, [6] based on similarity retrieval techniques [7] and fuzzy languages [8]. The main advantage of this approach is that similar pictures are stored logically close to each other by using quantitative similarity measures. Thus, for answering queries, the amount of picture data needed to be searched can be reduced and the retrieval time can be improved. In addition, in a pictorial database, very often it is desired to find pictures (or feature vectors, histograms, etc.) that are most similar to or most dissimilar [9] to a test picture (or feature vector). Using similarity measures, one can not only store similar pictures logically or physically close to each other in order to improve retrieval or updating efficiency, one can also use such similarity measures to answer fuzzy queries involving nonexact retrieval conditions. In this paper, similarity directed pictorial databases involving geometric figures, chromosome images, [10] leukocyte images, cardiomyopathy images, and satellite images [11] are presented as illustrative examples.

Retinal blood vessel segmentation using fully convolutional network with transfer learning.

PubMed

Jiang, Zhexin; Zhang, Hao; Wang, Yi; Ko, Seok-Bum

2018-04-26

Since the retinal blood vessel has been acknowledged as an indispensable element in both ophthalmological and cardiovascular disease diagnosis, the accurate segmentation of the retinal vessel tree has become the prerequisite step for automated or computer-aided diagnosis systems. In this paper, a supervised method is presented based on a pre-trained fully convolutional network through transfer learning. This proposed method has simplified the typical retinal vessel segmentation problem from full-size image segmentation to regional vessel element recognition and result merging. Meanwhile, additional unsupervised image post-processing techniques are applied to this proposed method so as to refine the final result. Extensive experiments have been conducted on DRIVE, STARE, CHASE_DB1 and HRF databases, and the accuracy of the cross-database test on these four databases is state-of-the-art, which also presents the high robustness of the proposed approach. This successful result has not only contributed to the area of automated retinal blood vessel segmentation but also supports the effectiveness of transfer learning when applying deep learning technique to medical imaging. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deep neural network features for horses identity recognition using multiview horses' face pattern

NASA Astrophysics Data System (ADS)

Jarraya, Islem; Ouarda, Wael; Alimi, Adel M.

2017-03-01

To control the state of horses in the born, breeders needs a monitoring system with a surveillance camera that can identify and distinguish between horses. We proposed in [5] a method of horse's identification at a distance using the frontal facial biometric modality. Due to the change of views, the face recognition becomes more difficult. In this paper, the number of images used in our THoDBRL'2015 database (Tunisian Horses DataBase of Regim Lab) is augmented by adding other images of other views. Thus, we used front, right and left profile face's view. Moreover, we suggested an approach for multiview face recognition. First, we proposed to use the Gabor filter for face characterization. Next, due to the augmentation of the number of images, and the large number of Gabor features, we proposed to test the Deep Neural Network with the auto-encoder to obtain the more pertinent features and to reduce the size of features vector. Finally, we performed the proposed approach on our THoDBRL'2015 database and we used the linear SVM for classification.

Application of furniture images selection based on neural network

NASA Astrophysics Data System (ADS)

Wang, Yong; Gao, Wenwen; Wang, Ying

2018-05-01

In the construction of 2 million furniture image databases, aiming at the problem of low quality of database, a combination of CNN and Metric learning algorithm is proposed, which makes it possible to quickly and accurately remove duplicate and irrelevant samples in the furniture image database. Solve problems that images screening method is complex, the accuracy is not high, time-consuming is long. Deep learning algorithm achieve excellent image matching ability in actual furniture retrieval applications after improving data quality.

Supporting reputation based trust management enhancing security layer for cloud service models

NASA Astrophysics Data System (ADS)

Karthiga, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

In the existing system trust between cloud providers and consumers is inadequate to establish the service level agreement though the consumer’s response is good cause to assess the overall reliability of cloud services. Investigators recognized the significance of trust can be managed and security can be provided based on feedback collected from participant. In this work a face recognition system that helps to identify the user effectively. So we use an image comparison algorithm where the user face is captured during registration time and get stored in database. With that original image we compare it with the sample image that is already stored in database. If both the image get matched then the users are identified effectively. When the confidential data are subcontracted to the cloud, data holders will become worried about the confidentiality of their data in the cloud. Encrypting the data before subcontracting has been regarded as the important resources of keeping user data privacy beside the cloud server. So in order to keep the data secure we use an AES algorithm. Symmetric-key algorithms practice a shared key concept, keeping data secret requires keeping this key secret. So only the user with private key can decrypt data.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

Automated detection of microcalcification clusters in mammograms

NASA Astrophysics Data System (ADS)

Karale, Vikrant A.; Mukhopadhyay, Sudipta; Singh, Tulika; Khandelwal, Niranjan; Sadhu, Anup

2017-03-01

Mammography is the most efficient modality for detection of breast cancer at early stage. Microcalcifications are tiny bright spots in mammograms and can often get missed by the radiologist during diagnosis. The presence of microcalcification clusters in mammograms can act as an early sign of breast cancer. This paper presents a completely automated computer-aided detection (CAD) system for detection of microcalcification clusters in mammograms. Unsharp masking is used as a preprocessing step which enhances the contrast between microcalcifications and the background. The preprocessed image is thresholded and various shape and intensity based features are extracted. Support vector machine (SVM) classifier is used to reduce the false positives while preserving the true microcalcification clusters. The proposed technique is applied on two different databases i.e DDSM and private database. The proposed technique shows good sensitivity with moderate false positives (FPs) per image on both databases.

Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images.

PubMed

Li, Wei; Cao, Peng; Zhao, Dazhe; Wang, Junbo

2016-01-01

Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for nodule classification, which has an advantage of autolearning representation and strong generalization ability. A specified network structure for nodule images is proposed to solve the recognition of three types of nodules, that is, solid, semisolid, and ground glass opacity (GGO). Deep convolutional neural networks are trained by 62,492 regions-of-interest (ROIs) samples including 40,772 nodules and 21,720 nonnodules from the Lung Image Database Consortium (LIDC) database. Experimental results demonstrate the effectiveness of the proposed method in terms of sensitivity and overall accuracy and that it consistently outperforms the competing methods.

An interactive system for computer-aided diagnosis of breast masses.

PubMed

Wang, Xingwei; Li, Lihua; Liu, Wei; Xu, Weidong; Lederman, Dror; Zheng, Bin

2012-10-01

Although mammography is the only clinically accepted imaging modality for screening the general population to detect breast cancer, interpreting mammograms is difficult with lower sensitivity and specificity. To provide radiologists "a visual aid" in interpreting mammograms, we developed and tested an interactive system for computer-aided detection and diagnosis (CAD) of mass-like cancers. Using this system, an observer can view CAD-cued mass regions depicted on one image and then query any suspicious regions (either cued or not cued by CAD). CAD scheme automatically segments the suspicious region or accepts manually defined region and computes a set of image features. Using content-based image retrieval (CBIR) algorithm, CAD searches for a set of reference images depicting "abnormalities" similar to the queried region. Based on image retrieval results and a decision algorithm, a classification score is assigned to the queried region. In this study, a reference database with 1,800 malignant mass regions and 1,800 benign and CAD-generated false-positive regions was used. A modified CBIR algorithm with a new function of stretching the attributes in the multi-dimensional space and decision scheme was optimized using a genetic algorithm. Using a leave-one-out testing method to classify suspicious mass regions, we compared the classification performance using two CBIR algorithms with either equally weighted or optimally stretched attributes. Using the modified CBIR algorithm, the area under receiver operating characteristic curve was significantly increased from 0.865 ± 0.006 to 0.897 ± 0.005 (p < 0.001). This study demonstrated the feasibility of developing an interactive CAD system with a large reference database and achieving improved performance.

An implementation of wireless medical image transmission system on mobile devices.

PubMed

Lee, SangBock; Lee, Taesoo; Jin, Gyehwan; Hong, Juhyun

2008-12-01

The advanced technology of computing system was followed by the rapid improvement of medical instrumentation and patient record management system. The typical examples are hospital information system (HIS) and picture archiving and communication system (PACS), which computerized the management procedure of medical records and images in hospital. Because these systems were built and used in hospitals, doctors out of hospital have problems to access them immediately on emergent cases. To solve these problems, this paper addressed the realization of system that could transmit the images acquired by medical imaging systems in hospital to the remote doctors' handheld PDA's using CDMA cellular phone network. The system consists of server and PDA. The server was developed to manage the accounts of doctors and patients and allocate the patient images to each doctor. The PDA was developed to display patient images through remote server connection. To authenticate the personal user, remote data access (RDA) method was used in PDA accessing the server database and file transfer protocol (FTP) was used to download patient images from the remove server. In laboratory experiments, it was calculated to take ninety seconds to transmit thirty images with 832 x 488 resolution and 24 bit depth and 0.37 Mb size. This result showed that the developed system has no problems for remote doctors to receive and review the patient images immediately on emergent cases.

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.

An integrated multimedia medical information network system.

PubMed

Yamamoto, K; Makino, J; Sasagawa, N; Nagira, M

1998-01-01

An integrated multimedia medical information network system at Shimane Medical university has been developed to organize medical information generated from each section and provide information services useful for education, research and clinical practice. The report describes the outline of our system. It is designed to serve as a distributed database for electronic medical records and images. We are developing the MML engine that is to be linked to the world wide web (WWW) network system. To the users, this system will present an integrated multimedia representation of the patient records, providing access to both the image and text-based data required for an effective clinical decision making and medical education.

Footprint Representation of Planetary Remote Sensing Data

NASA Astrophysics Data System (ADS)

Walter, S. H. G.; Gasselt, S. V.; Michael, G.; Neukum, G.

The geometric outline of remote sensing image data, the so called footprint, can be represented as a number of coordinate tuples. These polygons are associated with according attribute information such as orbit name, ground- and image resolution, solar longitude and illumination conditions to generate a powerful base for classification of planetary experiment data. Speed, handling and extended capabilites are the reasons for using geodatabases to store and access these data types. Techniques for such a spatial database of footprint data are demonstrated using the Relational Database Management System (RDBMS) PostgreSQL, spatially enabled by the PostGIS extension. Exemplary, footprints of the HRSC and OMEGA instruments, both onboard ESA's Mars Express Orbiter, are generated and connected to attribute information. The aim is to provide high-resolution footprints of the OMEGA instrument to the science community for the first time and make them available for web-based mapping applications like the "Planetary Interactive GIS-on-the-Web Analyzable Database" (PIG- WAD), produced by the USGS. Map overlays with HRSC or other instruments like MOC and THEMIS (footprint maps are already available for these instruments and can be integrated into the database) allow on-the-fly intersection and comparison as well as extended statistics of the data. Footprint polygons are generated one by one using standard software provided by the instrument teams. Attribute data is calculated and stored together with the geometric information. In the case of HRSC, the coordinates of the footprints are already available in the VICAR label of each image file. Using the VICAR RTL and PostgreSQL's libpq C library they are loaded into the database using the Well-Known Text (WKT) notation by the Open Geospatial Consortium, Inc. (OGC). For the OMEGA instrument, image data is read using IDL routines developed and distributed by the OMEGA team. Image outlines are exported together with relevant attribute data to the industry standard Shapefile format. These files are translated to a Structured Query Language (SQL) command sequence suitable for insertion into the PostGIS/PostgrSQL database using the shp2pgsql data loader provided by the PostGIS software. PostgreSQL's advanced features such as geometry types, rules, operators and functions allow complex spatial queries and on-the-fly processing of data on DBMS level e.g. generalisation of the outlines. Processing done by the DBMS, visualisation via GIS systems and utilisation for web-based applications like mapservers will be demonstrated.

Molecular Imaging and Contrast Agent Database (MICAD): evolution and progress.

PubMed

Chopra, Arvind; Shan, Liang; Eckelman, W C; Leung, Kam; Latterner, Martin; Bryant, Stephen H; Menkens, Anne

2012-02-01

The purpose of writing this review is to showcase the Molecular Imaging and Contrast Agent Database (MICAD; www.micad.nlm.nih.gov ) to students, researchers, and clinical investigators interested in the different aspects of molecular imaging. This database provides freely accessible, current, online scientific information regarding molecular imaging (MI) probes and contrast agents (CA) used for positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging, X-ray/computed tomography, optical imaging and ultrasound imaging. Detailed information on >1,000 agents in MICAD is provided in a chapter format and can be accessed through PubMed. Lists containing >4,250 unique MI probes and CAs published in peer-reviewed journals and agents approved by the United States Food and Drug Administration as well as a comma separated values file summarizing all chapters in the database can be downloaded from the MICAD homepage. Users can search for agents in MICAD on the basis of imaging modality, source of signal/contrast, agent or target category, pre-clinical or clinical studies, and text words. Chapters in MICAD describe the chemical characteristics (structures linked to PubChem), the in vitro and in vivo activities, and other relevant information regarding an imaging agent. All references in the chapters have links to PubMed. A Supplemental Information Section in each chapter is available to share unpublished information regarding an agent. A Guest Author Program is available to facilitate rapid expansion of the database. Members of the imaging community registered with MICAD periodically receive an e-mail announcement (eAnnouncement) that lists new chapters uploaded to the database. Users of MICAD are encouraged to provide feedback, comments, or suggestions for further improvement of the database by writing to the editors at micad@nlm.nih.gov.

Molecular Imaging and Contrast Agent Database (MICAD): Evolution and Progress

PubMed Central

Chopra, Arvind; Shan, Liang; Eckelman, W. C.; Leung, Kam; Latterner, Martin; Bryant, Stephen H.; Menkens, Anne

2011-01-01

The purpose of writing this review is to showcase the Molecular Imaging and Contrast Agent Database (MICAD; www.micad.nlm.nih.gov) to students, researchers and clinical investigators interested in the different aspects of molecular imaging. This database provides freely accessible, current, online scientific information regarding molecular imaging (MI) probes and contrast agents (CA) used for positron emission tomography, single-photon emission computed tomography, magnetic resonance imaging, x-ray/computed tomography, optical imaging and ultrasound imaging. Detailed information on >1000 agents in MICAD is provided in a chapter format and can be accessed through PubMed. Lists containing >4250 unique MI probes and CAs published in peer-reviewed journals and agents approved by the United States Food and Drug Administration (FDA) as well as a CSV file summarizing all chapters in the database can be downloaded from the MICAD homepage. Users can search for agents in MICAD on the basis of imaging modality, source of signal/contrast, agent or target category, preclinical or clinical studies, and text words. Chapters in MICAD describe the chemical characteristics (structures linked to PubChem), the in vitro and in vivo activities and other relevant information regarding an imaging agent. All references in the chapters have links to PubMed. A Supplemental Information Section in each chapter is available to share unpublished information regarding an agent. A Guest Author Program is available to facilitate rapid expansion of the database. Members of the imaging community registered with MICAD periodically receive an e-mail announcement (eAnnouncement) that lists new chapters uploaded to the database. Users of MICAD are encouraged to provide feedback, comments or suggestions for further improvement of the database by writing to the editors at: micad@nlm.nih.gov PMID:21989943

The SSABLE system - Automated archive, catalog, browse and distribution of satellite data in near-real time

NASA Technical Reports Server (NTRS)

Simpson, James J.; Harkins, Daniel N.

1993-01-01

Historically, locating and browsing satellite data has been a cumbersome and expensive process. This has impeded the efficient and effective use of satellite data in the geosciences. SSABLE is a new interactive tool for the archive, browse, order, and distribution of satellite date based upon X Window, high bandwidth networks, and digital image rendering techniques. SSABLE provides for automatically constructing relational database queries to archived image datasets based on time, data, geographical location, and other selection criteria. SSABLE also provides a visual representation of the selected archived data for viewing on the user's X terminal. SSABLE is a near real-time system; for example, data are added to SSABLE's database within 10 min after capture. SSABLE is network and machine independent; it will run identically on any machine which satisfies the following three requirements: 1) has a bitmapped display (monochrome or greater); 2) is running the X Window system; and 3) is on a network directly reachable by the SSABLE system. SSABLE has been evaluated at over 100 international sites. Network response time in the United States and Canada varies between 4 and 7 s for browse image updates; reported transmission times to Europe and Australia typically are 20-25 s.

Structured Forms Reference Set of Binary Images (SFRS)

National Institute of Standards and Technology Data Gateway

NIST Structured Forms Reference Set of Binary Images (SFRS) (Web, free access)   The NIST Structured Forms Database (Special Database 2) consists of 5,590 pages of binary, black-and-white images of synthesized documents. The documents in this database are 12 different tax forms from the IRS 1040 Package X for the year 1988.

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

How to design a horizontal patient-focused hospital.

PubMed

Murphy, E C; Ruflin, P

1993-05-01

Work Imaging is an executive information system for analyzing the cost effectiveness and efficiency of work processes and structures in health care. Advanced Work Imaging relational database technology allows managers and employees to take a sample work activities profile organization-wide. This is married to financial and organizational data to produce images of work within and across all functions, departments, and levels. The images are benchmarked against best practice data to provide insight on the quality and cost efficiency of work practice patterns, from individual roles to departmental skill mix to organization-wide service processes.

Paradise: A Parallel Information System for EOSDIS

NASA Technical Reports Server (NTRS)

DeWitt, David

1996-01-01

The Paradise project was begun-in 1993 in order to explore the application of the parallel and object-oriented database system technology developed as a part of the Gamma, Exodus. and Shore projects to the design and development of a scaleable, geo-spatial database system for storing both massive spatial and satellite image data sets. Paradise is based on an object-relational data model. In addition to the standard attribute types such as integers, floats, strings and time, Paradise also provides a set of and multimedia data types, designed to facilitate the storage and querying of complex spatial and multimedia data sets. An individual tuple can contain any combination of this rich set of data types. For example, in the EOSDIS context, a tuple might mix terrain and map data for an area along with the latest satellite weather photo of the area. The use of a geo-spatial metaphor simplifies the task of fusing disparate forms of data from multiple data sources including text, image, map, and video data sets.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

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

NONE

2011-02-15

Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.more » Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,''''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule{>=}3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.« less

Low-altitude photographic transects of the Arctic Network of National Park Units and Selawik National Wildlife Refuge, Alaska, July 2013

USGS Publications Warehouse

Marcot, Bruce G.; Jorgenson, M. Torre; DeGange, Anthony R.

2014-01-01

5. A Canon® Rebel 3Ti with a Sigma zoom lens (18–200 mm focal length). The Drift® HD-170 and GoPro® Hero3 cameras were secured to the struts and underwing for nadir (direct downward) imaging. The Panasonic® and Canon® cameras were each hand-held for oblique-angle landscape images, shooting through the airplanes’ windows, targeting both general landscape conditions as well as landscape features of special interest, such as tundra fire scars and landslips. The Drift® and GoPro® cameras each were set for time-lapse photography at 5-second intervals for overlapping coverage. Photographs from all cameras (100 percent .jpg format) were date- and time-synchronized to geographic positioning system waypoints taken during the flights, also at 5-second intervals, providing precise geotagging (latitude-longitude) of all files. All photographs were adjusted for color saturation and gamma, and nadir photographs were corrected for lens distortion for the Drift® and GoPro® cameras’ 170° wide-angle distortion. EXIF (exchangeable image file format) data on camera settings and geotagging were extracted into spreadsheet databases. An additional 1 hour, 20 minutes, and 43 seconds of high-resolution videos were recorded at 60 frames per second with the GoPro® camera along selected transect segments, and also were image-adjusted and corrected for lens distortion. Geotagged locations of 12,395 nadir photographs from the Drift® and GoPro® cameras were overlayed in a geographic information system (ArcMap 10.0) onto a map of 44 ecotypes (land- and water-cover types) of the Arctic Network study area. Presence and area of each ecotype occurring within a geographic information system window centered on the location of each photograph were recorded and included in the spreadsheet databases. All original and adjusted photographs, videos, geographic positioning system flight tracks, and photograph databases are available by contacting ascweb@usgs.gov.

Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

NASA Astrophysics Data System (ADS)

Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

2017-10-01

Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

Projecting 2D gene expression data into 3D and 4D space.

PubMed

Gerth, Victor E; Katsuyama, Kaori; Snyder, Kevin A; Bowes, Jeff B; Kitayama, Atsushi; Ueno, Naoto; Vize, Peter D

2007-04-01

Video games typically generate virtual 3D objects by texture mapping an image onto a 3D polygonal frame. The feeling of movement is then achieved by mathematically simulating camera movement relative to the polygonal frame. We have built customized scripts that adapt video game authoring software to texture mapping images of gene expression data onto b-spline based embryo models. This approach, known as UV mapping, associates two-dimensional (U and V) coordinates within images to the three dimensions (X, Y, and Z) of a b-spline model. B-spline model frameworks were built either from confocal data or de novo extracted from 2D images, once again using video game authoring approaches. This system was then used to build 3D models of 182 genes expressed in developing Xenopus embryos and to implement these in a web-accessible database. Models can be viewed via simple Internet browsers and utilize openGL hardware acceleration via a Shockwave plugin. Not only does this database display static data in a dynamic and scalable manner, the UV mapping system also serves as a method to align different images to a common framework, an approach that may make high-throughput automated comparisons of gene expression patterns possible. Finally, video game systems also have elegant methods for handling movement, allowing biomechanical algorithms to drive the animation of models. With further development, these biomechanical techniques offer practical methods for generating virtual embryos that recapitulate morphogenesis.

NASA Tech Briefs, June 2013

NASA Technical Reports Server (NTRS)

2013-01-01

Topics include: Cloud Absorption Radiometer Autonomous Navigation System - CANS, Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis, Discrete Data Qualification System and Method Comprising Noise Series Fault Detection, Simple Laser Communications Terminal for Downlink from Earth Orbit at Rates Exceeding 10 Gb/s, Application Program Interface for the Orion Aerodynamics Database, Hyperspectral Imager-Tracker, Web Application Software for Ground Operations Planning Database (GOPDb) Management, Software Defined Radio with Parallelized Software Architecture, Compact Radar Transceiver with Included Calibration, Software Defined Radio with Parallelized Software Architecture, Phase Change Material Thermal Power Generator, The Thermal Hogan - A Means of Surviving the Lunar Night, Micromachined Active Magnetic Regenerator for Low-Temperature Magnetic Coolers, Nano-Ceramic Coated Plastics, Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use, Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO, Dual-Compartment Inflatable Suitlock, Modular Connector Keying Concept, Genesis Ultrapure Water Megasonic Wafer Spin Cleaner, Piezoelectrically Initiated Pyrotechnic Igniter, Folding Elastic Thermal Surface - FETS, Multi-Pass Quadrupole Mass Analyzer, Lunar Sulfur Capture System, Environmental Qualification of a Single-Crystal Silicon Mirror for Spaceflight Use, Planar Superconducting Millimeter-Wave/Terahertz Channelizing Filter, Qualification of UHF Antenna for Extreme Martian Thermal Environments, Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project, ISS Live!, Space Operations Learning Center (SOLC) iPhone/iPad Application, Software to Compare NPP HDF5 Data Files, Planetary Data Systems (PDS) Imaging Node Atlas II, Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit, Translating MAPGEN to ASPEN for MER, Support Routines for In Situ Image Processing, and Semi-Supervised Eigenbasis Novelty Detection.

Method for secure electronic voting system: face recognition based approach

NASA Astrophysics Data System (ADS)

Alim, M. Affan; Baig, Misbah M.; Mehboob, Shahzain; Naseem, Imran

2017-06-01

In this paper, we propose a framework for low cost secure electronic voting system based on face recognition. Essentially Local Binary Pattern (LBP) is used for face feature characterization in texture format followed by chi-square distribution is used for image classification. Two parallel systems are developed based on smart phone and web applications for face learning and verification modules. The proposed system has two tire security levels by using person ID followed by face verification. Essentially class specific threshold is associated for controlling the security level of face verification. Our system is evaluated three standard databases and one real home based database and achieve the satisfactory recognition accuracies. Consequently our propose system provides secure, hassle free voting system and less intrusive compare with other biometrics.

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

Shimizu, Y; Yoon, Y; Iwase, K

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints thatmore » could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.« less

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

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.

Image matching algorithms for breech face marks and firing pins in a database of spent cartridge cases of firearms.

PubMed

Geradts, Z J; Bijhold, J; Hermsen, R; Murtagh, F

2001-06-01

On the market several systems exist for collecting spent ammunition data for forensic investigation. These databases store images of cartridge cases and the marks on them. Image matching is used to create hit lists that show which marks on a cartridge case are most similar to another cartridge case. The research in this paper is focused on the different methods of feature selection and pattern recognition that can be used for optimizing the results of image matching. The images are acquired by side light images for the breech face marks and by ring light for the firing pin impression. For these images a standard way of digitizing the images used. For the side light images and ring light images this means that the user has to position the cartridge case in the same position according to a protocol. The positioning is important for the sidelight, since the image that is obtained of a striation mark depends heavily on the angle of incidence of the light. In practice, it appears that the user positions the cartridge case with +/-10 degrees accuracy. We tested our algorithms using 49 cartridge cases of 19 different firearms, where the examiner determined that they were shot with the same firearm. For testing, these images were mixed with a database consisting of approximately 4900 images that were available from the Drugfire database of different calibers.In cases where the registration and the light conditions among those matching pairs was good, a simple computation of the standard deviation of the subtracted gray levels, delivered the best-matched images. For images that were rotated and shifted, we have implemented a "brute force" way of registration. The images are translated and rotated until the minimum of the standard deviation of the difference is found. This method did not result in all relevant matches in the top position. This is caused by the effect that shadows and highlights are compared in intensity. Since the angle of incidence of the light will give a different intensity profile, this method is not optimal. For this reason a preprocessing of the images was required. It appeared that the third scale of the "à trous" wavelet transform gives the best results in combination with brute force. Matching the contents of the images is less sensitive to the variation of the lighting. The problem with the brute force method is however that the time for calculation for 49 cartridge cases to compare between them, takes over 1 month of computing time on a Pentium II-computer with 333MHz. For this reason a faster approach is implemented: correlation in log polar coordinates. This gave similar results as the brute force calculation, however it was computed in 24h for a complete database with 4900 images.A fast pre-selection method based on signatures is carried out that is based on the Kanade Lucas Tomasi (KLT) equation. The positions of the points computed with this method are compared. In this way, 11 of the 49 images were in the top position in combination with the third scale of the à trous equation. It depends however on the light conditions and the prominence of the marks if correct matches are found in the top ranked position. All images were retrieved in the top 5% of the database. This method takes only a few minutes for the complete database if, and can be optimized for comparison in seconds if the location of points are stored in files. For further improvement, it is useful to have the refinement in which the user selects the areas that are relevant on the cartridge case for their marks. This is necessary if this cartridge case is damaged and other marks that are not from the firearm appear on it.

Analysis and Implementation of Methodologies for the Monitoring of Changes in Eye Fundus Images

NASA Astrophysics Data System (ADS)

Gelroth, A.; Rodríguez, D.; Salvatelli, A.; Drozdowicz, B.; Bizai, G.

2011-12-01

We present a support system for changes detection in fundus images of the same patient taken at different time intervals. This process is useful for monitoring pathologies lasting for long periods of time, as are usually the ophthalmologic. We propose a flow of preprocessing, processing and postprocessing applied to a set of images selected from a public database, presenting pathological advances. A test interface was developed designed to select the images to be compared in order to apply the different methods developed and to display the results. We measure the system performance in terms of sensitivity, specificity and computation times. We have obtained good results, higher than 84% for the first two parameters and processing times lower than 3 seconds for 512x512 pixel images. For the specific case of detection of changes associated with bleeding, the system responds with sensitivity and specificity over 98%.

Unified Planetary Coordinates System: A Searchable Database of Geodetic Information

NASA Technical Reports Server (NTRS)

Becker, K. J.a; Gaddis, L. R.; Soderblom, L. A.; Kirk, R. L.; Archinal, B. A.; Johnson, J. R.; Anderson, J. A.; Bowman-Cisneros, E.; LaVoie, S.; McAuley, M.

2005-01-01

Over the past 40 years, an enormous quantity of orbital remote sensing data has been collected for Mars from many missions and instruments. Unfortunately these datasets currently exist in a wide range of disparate coordinate systems, making it extremely difficult for the scientific community to easily correlate, combine, and compare data from different Mars missions and instruments. As part of our work for the PDS Imaging Node and on behalf of the USGS Astrogeology Team, we are working to solve this problem and to provide the NASA scientific research community with easy access to Mars orbital data in a unified, consistent coordinate system along with a wide variety of other key geometric variables. The Unified Planetary Coordinates (UPC) system is comprised of two main elements: (1) a database containing Mars orbital remote sensing data computed using a uniform coordinate system, and (2) a process by which continual maintainance and updates to the contents of the database are performed.

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.

Star-Mapping Tools Enable Tracking of Endangered Animals

NASA Technical Reports Server (NTRS)

2009-01-01

Software programmer Jason Holmberg of Portland, Oregon, partnered with a Goddard Space Flight Center astrophysicist to develop a method for tracking the elusive whale shark using the unique spot patterns on the fish s skin. Employing a star-mapping algorithm originally designed for the Hubble Space Telescope, Holmberg created the Shepherd Project, a photograph database and pattern-matching system that can identify whale sharks by their spots and match images contributed to the database by photographers from around the world. The system has been adapted for tracking other rare and endangered animals, including polar bears and ocean sunfish.

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

Increasing Receipt of High-Tech/High-Cost Imaging and Its Determinants in the Last Month of Taiwanese Patients With Metastatic Cancer, 2001-2010: A Retrospective Cohort Study.

PubMed

Liu, Tsang-Wu; Hung, Yen-Ni; Soong, Thomas C; Tang, Siew Tzuh

2015-08-01

One strategy for controlling the skyrocketing costs of cancer care may be to target high-tech/high-cost imaging at the end of life (EOL). This population-based study investigated receipt of high-tech/high-cost imaging and its determinants for Taiwanese patients with metastatic cancer in their last month of life.Individual patient-level data were linked with encrypted identification numbers from computerized administrative data in Taiwan, that is, the National Register of Deaths Database, Cancer Registration System database, and National Health Insurance claims datasets, Database of Medical Care Institutions Status, and national census statistics (population/household income). We identified receipt of computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and radionuclide bone scans (BSs) for 236,911 Taiwanese cancer decedents with metastatic disease, 2001 to 2010. Associations of patient, physician, hospital, and regional factors with receiving CT, MRI, and bone scan in the last month of life were evaluated by multilevel generalized linear-mixed models.Over one-third (average [range]: 36.11% [33.07%-37.31%]) of patients with metastatic cancer received at least 1 high-tech/high-cost imaging modality in their last month (usage rates for CT, MRI, PET, and BS were 31.05%, 5.81%, 0.25%, and 8.15%, respectively). In 2001 to 2010, trends of receipt increased for CT (27.96-32.22%), MRI (4.34-6.70%), and PET (0.00-0.62%), but decreased for BS (9.47-6.57%). Facilitative determinants with consistent trends for at least 2 high-tech/high-cost imaging modalities were male gender, younger age, married, rural residence, lung cancer diagnosis, dying within 1 to 2 years of diagnosis, not under medical oncology care, and receiving care at a teaching hospital with a larger volume of terminally ill cancer patients and greater EOL care intensity. Undergoing high-tech/high-cost imaging at EOL generally was not associated with regional characteristics, healthcare resources, and EOL care intensity.To more effectively use high-tech/high-cost imaging at EOL, clinical and financial interventions should target nonmedical oncologists/hematologists affiliated with teaching hospitals that tend to aggressively treat high volumes of terminally ill cancer patients, thereby avoiding unnecessary EOL care spending and transforming healthcare systems into affordable high-quality cancer care delivery systems.

Medical Image Databases

PubMed Central

Tagare, Hemant D.; Jaffe, C. Carl; Duncan, James

1997-01-01

Abstract Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema. PMID:9147338

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

DOEpatents

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

2013-08-06

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

Informatics in radiology: Efficiency metrics for imaging device productivity.

PubMed

Hu, Mengqi; Pavlicek, William; Liu, Patrick T; Zhang, Muhong; Langer, Steve G; Wang, Shanshan; Place, Vicki; Miranda, Rafael; Wu, Teresa Tong

2011-01-01

Acute awareness of the costs associated with medical imaging equipment is an ever-present aspect of the current healthcare debate. However, the monitoring of productivity associated with expensive imaging devices is likely to be labor intensive, relies on summary statistics, and lacks accepted and standardized benchmarks of efficiency. In the context of the general Six Sigma DMAIC (design, measure, analyze, improve, and control) process, a World Wide Web-based productivity tool called the Imaging Exam Time Monitor was developed to accurately and remotely monitor imaging efficiency with use of Digital Imaging and Communications in Medicine (DICOM) combined with a picture archiving and communication system. Five device efficiency metrics-examination duration, table utilization, interpatient time, appointment interval time, and interseries time-were derived from DICOM values. These metrics allow the standardized measurement of productivity, to facilitate the comparative evaluation of imaging equipment use and ongoing efforts to improve efficiency. A relational database was constructed to store patient imaging data, along with device- and examination-related data. The database provides full access to ad hoc queries and can automatically generate detailed reports for administrative and business use, thereby allowing staff to monitor data for trends and to better identify possible changes that could lead to improved productivity and reduced costs in association with imaging services. © RSNA, 2011.

Fast and automatic algorithm for optic disc extraction in retinal images using principle-component-analysis-based preprocessing and curvelet transform.

PubMed

Shahbeig, Saleh; Pourghassem, Hossein

2013-01-01

Optic disc or optic nerve (ON) head extraction in retinal images has widespread applications in retinal disease diagnosis and human identification in biometric systems. This paper introduces a fast and automatic algorithm for detecting and extracting the ON region accurately from the retinal images without the use of the blood-vessel information. In this algorithm, to compensate for the destructive changes of the illumination and also enhance the contrast of the retinal images, we estimate the illumination of background and apply an adaptive correction function on the curvelet transform coefficients of retinal images. In other words, we eliminate the fault factors and pave the way to extract the ON region exactly. Then, we detect the ON region from retinal images using the morphology operators based on geodesic conversions, by applying a proper adaptive correction function on the reconstructed image's curvelet transform coefficients and a novel powerful criterion. Finally, using a local thresholding on the detected area of the retinal images, we extract the ON region. The proposed algorithm is evaluated on available images of DRIVE and STARE databases. The experimental results indicate that the proposed algorithm obtains an accuracy rate of 100% and 97.53% for the ON extractions on DRIVE and STARE databases, respectively.

Quality labeled faces in the wild (QLFW): a database for studying face recognition in real-world environments

NASA Astrophysics Data System (ADS)

Karam, Lina J.; Zhu, Tong

2015-03-01

The varying quality of face images is an important challenge that limits the effectiveness of face recognition technology when applied in real-world applications. Existing face image databases do not consider the effect of distortions that commonly occur in real-world environments. This database (QLFW) represents an initial attempt to provide a set of labeled face images spanning the wide range of quality, from no perceived impairment to strong perceived impairment for face detection and face recognition applications. Types of impairment include JPEG2000 compression, JPEG compression, additive white noise, Gaussian blur and contrast change. Subjective experiments are conducted to assess the perceived visual quality of faces under different levels and types of distortions and also to assess the human recognition performance under the considered distortions. One goal of this work is to enable automated performance evaluation of face recognition technologies in the presence of different types and levels of visual distortions. This will consequently enable the development of face recognition systems that can operate reliably on real-world visual content in the presence of real-world visual distortions. Another goal is to enable the development and assessment of visual quality metrics for face images and for face detection and recognition applications.

An automatic chip structure optical inspection system for electronic components

NASA Astrophysics Data System (ADS)

Song, Zhichao; Xue, Bindang; Liang, Jiyuan; Wang, Ke; Chen, Junzhang; Liu, Yunhe

2018-01-01

An automatic chip structure inspection system based on machine vision is presented to ensure the reliability of electronic components. It consists of four major modules, including a metallographic microscope, a Gigabit Ethernet high-resolution camera, a control system and a high performance computer. An auto-focusing technique is presented to solve the problem that the chip surface is not on the same focusing surface under the high magnification of the microscope. A panoramic high-resolution image stitching algorithm is adopted to deal with the contradiction between resolution and field of view, caused by different sizes of electronic components. In addition, we establish a database to storage and callback appropriate parameters to ensure the consistency of chip images of electronic components with the same model. We use image change detection technology to realize the detection of chip images of electronic components. The system can achieve high-resolution imaging for chips of electronic components with various sizes, and clearly imaging for the surface of chip with different horizontal and standardized imaging for ones with the same model, and can recognize chip defects.

The LISS--a public database of common imaging signs of lung diseases for computer-aided detection and diagnosis research and medical education.

PubMed

Han, Guanghui; Liu, Xiabi; Han, Feifei; Santika, I Nyoman Tenaya; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2015-02-01

Lung computed tomography (CT) imaging signs play important roles in the diagnosis of lung diseases. In this paper, we review the significance of CT imaging signs in disease diagnosis and determine the inclusion criterion of CT scans and CT imaging signs of our database. We develop the software of abnormal regions annotation and design the storage scheme of CT images and annotation data. Then, we present a publicly available database of lung CT imaging signs, called LISS for short, which contains 271 CT scans and 677 abnormal regions in them. The 677 abnormal regions are divided into nine categories of common CT imaging signs of lung disease (CISLs). The ground truth of these CISLs regions and the corresponding categories are provided. Furthermore, to make the database publicly available, all private data in CT scans are eliminated or replaced with provisioned values. The main characteristic of our LISS database is that it is developed from a new perspective of CT imaging signs of lung diseases instead of commonly considered lung nodules. Thus, it is promising to apply to computer-aided detection and diagnosis research and medical education.

Dual energy CT: How well can pseudo-monochromatic imaging reduce metal artifacts?

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

Kuchenbecker, Stefan, E-mail: stefan.kuchenbecker@dkfz.de; Faby, Sebastian; Sawall, Stefan

2015-02-15

Purpose: Dual Energy CT (DECT) provides so-called monoenergetic images based on a linear combination of the original polychromatic images. At certain patient-specific energy levels, corresponding to certain patient- and slice-dependent linear combination weights, e.g., E = 160 keV corresponds to α = 1.57, a significant reduction of metal artifacts may be observed. The authors aimed at analyzing the method for its artifact reduction capabilities to identify its limitations. The results are compared with raw data-based processing. Methods: Clinical DECT uses a simplified version of monochromatic imaging by linearly combining the low and the high kV images and by assigning an energymore » to that linear combination. Those pseudo-monochromatic images can be used by radiologists to obtain images with reduced metal artifacts. The authors analyzed the underlying physics and carried out a series expansion of the polychromatic attenuation equations. The resulting nonlinear terms are responsible for the artifacts, but they are not linearly related between the low and the high kV scan: A linear combination of both images cannot eliminate the nonlinearities, it can only reduce their impact. Scattered radiation yields additional noncanceling nonlinearities. This method is compared to raw data-based artifact correction methods. To quantify the artifact reduction potential of pseudo-monochromatic images, they simulated the FORBILD abdomen phantom with metal implants, and they assessed patient data sets of a clinical dual source CT system (100, 140 kV Sn) containing artifacts induced by a highly concentrated contrast agent bolus and by metal. In each case, they manually selected an optimal α and compared it to a raw data-based material decomposition in case of simulation, to raw data-based material decomposition of inconsistent rays in case of the patient data set containing contrast agent, and to the frequency split normalized metal artifact reduction in case of the metal implant. For each case, the contrast-to-noise ratio (CNR) was assessed. Results: In the simulation, the pseudo-monochromatic images yielded acceptable artifact reduction results. However, the CNR in the artifact-reduced images was more than 60% lower than in the original polychromatic images. In contrast, the raw data-based material decomposition did not significantly reduce the CNR in the virtual monochromatic images. Regarding the patient data with beam hardening artifacts and with metal artifacts from small implants the pseudo-monochromatic method was able to reduce the artifacts, again with the downside of a significant CNR reduction. More intense metal artifacts, e.g., as those caused by an artificial hip joint, could not be suppressed. Conclusions: Pseudo-monochromatic imaging is able to reduce beam hardening, scatter, and metal artifacts in some cases but it cannot remove them. In all cases, the CNR is significantly reduced, thereby rendering the method questionable, unless special post processing algorithms are implemented to restore the high CNR from the original images (e.g., by using a frequency split technique). Raw data-based dual energy decomposition methods should be preferred, in particular, because the CNR penalty is almost negligible.« less

Implementation of a high-speed face recognition system that uses an optical parallel correlator.

PubMed

Watanabe, Eriko; Kodate, Kashiko

2005-02-10

We implement a fully automatic fast face recognition system by using a 1000 frame/s optical parallel correlator designed and assembled by us. The operational speed for the 1:N (i.e., matching one image against N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 s, including the preprocessing and postprocessing times. The binary real-only matched filter is devised for the sake of face recognition, and the system is optimized by the false-rejection rate (FRR) and the false-acceptance rate (FAR), according to 300 samples selected by the biometrics guideline. From trial 1:N identification experiments with the optical parallel correlator, we acquired low error rates of 2.6% FRR and 1.3% FAR. Facial images of people wearing thin glasses or heavy makeup that rendered identification difficult were identified with this system.

ARCADIA: a system for the integration of angiocardiographic data and images by an object-oriented DBMS.

PubMed

Pinciroli, F; Combi, C; Pozzi, G

1995-02-01

Use of data base techniques to store medical records has been going on for more than 40 years. Some aspects still remain unresolved, e.g., the management of textual data and image data within a single system. Object-orientation techniques applied to a database management system (DBMS) allow the definition of suitable data structures (e.g., to store digital images): some facilities allow the use of predefined structures when defining new ones. Currently available object-oriented DBMS, however, still need improvements both in the schema update and in the query facilities. This paper describes a prototype of a medical record that includes some multimedia features, managing both textual and image data. The prototype here described considers data from the medical records of patients subjected to percutaneous transluminal coronary artery angioplasty. We developed it on a Sun workstation with a Unix operating system and ONTOS as an object-oriented DBMS.

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

PubMed

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

2016-12-01

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

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.

DCT-based iris recognition.

PubMed

Monro, Donald M; Rakshit, Soumyadip; Zhang, Dexin

2007-04-01

This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent Correct Recognition Rate (CRR) and perfect Receiver-Operating Characteristic (ROC) Curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the False Acceptance Rate (FAR) and False Rejection Rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical Equal Error Rate (EER) is predicted to be as low as 2.59 x 10(-4) on the available data sets.

Searching for patterns in remote sensing image databases using neural networks

NASA Technical Reports Server (NTRS)

Paola, Justin D.; Schowengerdt, Robert A.

1995-01-01

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Medication order communication using fax and document-imaging technologies.

PubMed

Simonian, Armen I

2008-03-15

The implementation of fax and document-imaging technology to electronically communicate medication orders from nursing stations to the pharmacy is described. The evaluation of a commercially available pharmacy order imaging system to improve order communication and to make document retrieval more efficient led to the selection and customization of a system already licensed and used in seven affiliated hospitals. The system consisted of existing fax machines and document-imaging software that would capture images of written orders and send them from nursing stations to a central database server. Pharmacists would then retrieve the images and enter the orders in an electronic medical record system. The pharmacy representatives from all seven hospitals agreed on the configuration and functionality of the custom application. A 30-day trial of the order imaging system was successfully conducted at one of the larger institutions. The new system was then implemented at the remaining six hospitals over a period of 60 days. The transition from a paper-order system to electronic communication via a standardized pharmacy document management application tailored to the specific needs of this health system was accomplished. A health system with seven affiliated hospitals successfully implemented electronic communication and the management of inpatient paper-chart orders by using faxes and document-imaging technology. This standardized application eliminated the problems associated with the hand delivery of paper orders, the use of the pneumatic tube system, and the printing of traditional faxes.

No-reference quality assessment based on visual perception

NASA Astrophysics Data System (ADS)

Li, Junshan; Yang, Yawei; Hu, Shuangyan; Zhang, Jiao

2014-11-01

The visual quality assessment of images/videos is an ongoing hot research topic, which has become more and more important for numerous image and video processing applications with the rapid development of digital imaging and communication technologies. The goal of image quality assessment (IQA) algorithms is to automatically assess the quality of images/videos in agreement with human quality judgments. Up to now, two kinds of models have been used for IQA, namely full-reference (FR) and no-reference (NR) models. For FR models, IQA algorithms interpret image quality as fidelity or similarity with a perfect image in some perceptual space. However, the reference image is not available in many practical applications, and a NR IQA approach is desired. Considering natural vision as optimized by the millions of years of evolutionary pressure, many methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychological features of the human visual system (HVS). To reach this goal, researchers try to simulate HVS with image sparsity coding and supervised machine learning, which are two main features of HVS. A typical HVS captures the scenes by sparsity coding, and uses experienced knowledge to apperceive objects. In this paper, we propose a novel IQA approach based on visual perception. Firstly, a standard model of HVS is studied and analyzed, and the sparse representation of image is accomplished with the model; and then, the mapping correlation between sparse codes and subjective quality scores is trained with the regression technique of least squaresupport vector machine (LS-SVM), which gains the regressor that can predict the image quality; the visual metric of image is predicted with the trained regressor at last. We validate the performance of proposed approach on Laboratory for Image and Video Engineering (LIVE) database, the specific contents of the type of distortions present in the database are: 227 images of JPEG2000, 233 images of JPEG, 174 images of White Noise, 174 images of Gaussian Blur, 174 images of Fast Fading. The database includes subjective differential mean opinion score (DMOS) for each image. The experimental results show that the proposed approach not only can assess many kinds of distorted images quality, but also exhibits a superior accuracy and monotonicity.

Cephalometric landmark detection in dental x-ray images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Lee, Hansang; Park, Minseok; Kim, Junmo

2017-03-01

In dental X-ray images, an accurate detection of cephalometric landmarks plays an important role in clinical diagnosis, treatment and surgical decisions for dental problems. In this work, we propose an end-to-end deep learning system for cephalometric landmark detection in dental X-ray images, using convolutional neural networks (CNN). For detecting 19 cephalometric landmarks in dental X-ray images, we develop a detection system using CNN-based coordinate-wise regression systems. By viewing x- and y-coordinates of all landmarks as 38 independent variables, multiple CNN-based regression systems are constructed to predict the coordinate variables from input X-ray images. First, each coordinate variable is normalized by the length of either height or width of an image. For each normalized coordinate variable, a CNN-based regression system is trained on training images and corresponding coordinate variable, which is a variable to be regressed. We train 38 regression systems with the same CNN structure on coordinate variables, respectively. Finally, we compute 38 coordinate variables with these trained systems from unseen images and extract 19 landmarks by pairing the regressed coordinates. In experiments, the public database from the Grand Challenges in Dental X-ray Image Analysis in ISBI 2015 was used and the proposed system showed promising performance by successfully locating the cephalometric landmarks within considerable margins from the ground truths.

Predicting Database Requirements for Geographic Information Systems in the Year 2000: Long-Term Design Issues for GRASS

DTIC Science & Technology

1992-08-01

Image Processing. Reading, Massachusetts: Addison-Wesley (1977). Graefe, G., "Parallelizing the Volcano Query Processor," Proc. IEEE COMPCON 90...Approach to a Next Generation of Hypermedia System," Proc. IEEE COMPCON 90 (February 1990), pp 520-527. Jellinghaus, R., " Eiffel Linda: An Object

Creating a New Definition of Library Cooperation: Past, Present, and Future Models.

ERIC Educational Resources Information Center

Lenzini, Rebecca T.; Shaw, Ward

1991-01-01

Describes the creation and purpose of the Colorado Alliance of Research Libraries (CARL), the subsequent development of CARL Systems, and its current research projects. Topics discussed include online catalogs; UnCover, a journal article database; full text data; document delivery; visual images in computer systems; networks; and implications for…

A new method for the automatic retrieval of medical cases based on the RadLex ontology.

PubMed

Spanier, A B; Cohen, D; Joskowicz, L

2017-03-01

The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision-making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and textual information on the anatomy and pathology findings. The textual information, when available in standardized terminology, e.g., the RadLex ontology, and used in conjunction with the radiological images, provides a substantial advantage for M-CBIR systems. We present a new method for incorporating textual radiological findings from medical case reports in M-CBIR. The input is a database of medical cases, a query case, and the number of desired relevant cases. The output is an ordered list of the most relevant cases in the database. The method is based on a new case formulation, the Augmented RadLex Graph and an Anatomy-Pathology List. It uses a new case relatedness metric [Formula: see text] that prioritizes more specific medical terms in the RadLex tree over less specific ones and that incorporates the length of the query case. An experimental study on 8 CT queries from the 2015 VISCERAL 3D Case Retrieval Challenge database consisting of 1497 volumetric CT scans shows that our method has accuracy rates of 82 and 70% on the first 10 and 30 most relevant cases, respectively, thereby outperforming six other methods. The increasing amount of medical imaging data acquired in clinical practice constitutes a vast database of untapped diagnostically relevant information. This paper presents a new hybrid approach to retrieving the most relevant medical cases based on textual and image information.

Comparison of eye imaging pattern recognition using neural network

NASA Astrophysics Data System (ADS)

Bukhari, W. M.; Syed A., M.; Nasir, M. N. M.; Sulaima, M. F.; Yahaya, M. S.

2015-05-01

The beauty of eye recognition system that it is used in automatic identifying and verifies a human weather from digital images or video source. There are various behaviors of the eye such as the color of the iris, size of pupil and shape of the eye. This study represents the analysis, design and implementation of a system for recognition of eye imaging. All the eye images that had been captured from the webcam in RGB format must through several techniques before it can be input for the pattern and recognition processes. The result shows that the final value of weight and bias after complete training 6 eye images for one subject is memorized by the neural network system and be the reference value of the weight and bias for the testing part. The target classifies to 5 different types for 5 subjects. The eye images can recognize the subject based on the target that had been set earlier during the training process. When the values between new eye image and the eye image in the database are almost equal, it is considered the eye image is matched.

The Young Visual Binary Database

NASA Astrophysics Data System (ADS)

Prato, Lisa A.; Avilez, Ian; Allen, Thomas; Zoonematkermani, Saeid; Biddle, Lauren; Muzzio, Ryan; Wittal, Matthew; Schaefer, Gail; Simon, Michal

2017-01-01

We have obtained adaptive optics imaging and high-resolution H-band and in some cases K-band spectra of each component in close to 100 young multiple systems in the nearby star forming regions of Taurus, Ophiuchus, TW Hya, and Orion. The binary separations for the pairs in our sample range from 30 mas to 3 arcseconds. The imaging and most of our spectra were obtained with instruments behind adaptive optics systems in order to resolve even the closest companions. We are in the process of determining fundamental stellar and circumstellar properties, such as effective temperature, Vsin(i), veiling, and radial velocity, for each component in the entire sample. The beta version of our database includes systems in the Taurus region and provides plots, downloadable ascii spectra, and values of the stellar and circumstellar properties for both stars in each system. This resource is openly available to the community at http://jumar.lowell.edu/BinaryStars/. In this poster we describe initial results from our analysis of the survey data. Support for this research was provided in part by NSF award AST-1313399 and by NASA Keck KPDA funding.

Automated graphic image generation system for effective representation of infectious disease surveillance data.

PubMed

Inoue, Masashi; Hasegawa, Shinsaku; Suyama, Akihiko; Meshitsuka, Shunsuke

2003-11-01

Infectious disease surveillance schemes have been established to detect infectious disease outbreak in the early stages, to identify the causative viral strains, and to rapidly assess related morbidity and mortality. To make a scheme function well, two things are required. Firstly, it must have sufficient sensitivity and be timely to guarantee as short a delay as possible from collection to redistribution of information. Secondly, it must provide a good representation of the results of the surveillance. To do this, we have developed a database system that can redistribute the information via the Internet. The feature of this system is to automatically generate the graphic images based on the numerical data stored in the database by using Hypertext Preprocessor (PHP) script and Graphics Drawing (GD) library. It dynamically displays the information as a map or bar chart as well as a numerical impression according to the real time demand of the users. This system will be a useful tool for medical personnel and researchers working on infectious disease problems and will save significant time in the redistribution of information.

A novel computer-aided detection system for pulmonary nodule identification in CT images

NASA Astrophysics Data System (ADS)

Han, Hao; Li, Lihong; Wang, Huafeng; Zhang, Hao; Moore, William; Liang, Zhengrong

2014-03-01

Computer-aided detection (CADe) of pulmonary nodules from computer tomography (CT) scans is critical for assisting radiologists to identify lung lesions at an early stage. In this paper, we propose a novel approach for CADe of lung nodules using a two-stage vector quantization (VQ) scheme. The first-stage VQ aims to extract lung from the chest volume, while the second-stage VQ is designed to extract initial nodule candidates (INCs) within the lung volume. Then rule-based expert filtering is employed to prune obvious FPs from INCs, and the commonly-used support vector machine (SVM) classifier is adopted to further reduce the FPs. The proposed system was validated on 100 CT scans randomly selected from the 262 scans that have at least one juxta-pleural nodule annotation in the publicly available database - Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The two-stage VQ only missed 2 out of the 207 nodules at agreement level 1, and the INCs detection for each scan took about 30 seconds in average. Expert filtering reduced FPs more than 18 times, while maintaining a sensitivity of 93.24%. As it is trivial to distinguish INCs attached to pleural wall versus not on wall, we investigated the feasibility of training different SVM classifiers to further reduce FPs from these two kinds of INCs. Experiment results indicated that SVM classification over the entire set of INCs was in favor of, where the optimal operating of our CADe system achieved a sensitivity of 89.4% at a specificity of 86.8%.

Design of a Web-tool for diagnostic clinical trials handling medical imaging research.

PubMed

Baltasar Sánchez, Alicia; González-Sistal, Angel

2011-04-01

New clinical studies in medicine are based on patients and controls using different imaging diagnostic modalities. Medical information systems are not designed for clinical trials employing clinical imaging. Although commercial software and communication systems focus on storage of image data, they are not suitable for storage and mining of new types of quantitative data. We sought to design a Web-tool to support diagnostic clinical trials involving different experts and hospitals or research centres. The image analysis of this project is based on skeletal X-ray imaging. It involves a computerised image method using quantitative analysis of regions of interest in healthy bone and skeletal metastases. The database is implemented with ASP.NET 3.5 and C# technologies for our Web-based application. For data storage, we chose MySQL v.5.0, one of the most popular open source databases. User logins were necessary, and access to patient data was logged for auditing. For security, all data transmissions were carried over encrypted connections. This Web-tool is available to users scattered at different locations; it allows an efficient organisation and storage of data (case report form) and images and allows each user to know precisely what his task is. The advantages of our Web-tool are as follows: (1) sustainability is guaranteed; (2) network locations for collection of data are secured; (3) all clinical information is stored together with the original images and the results derived from processed images and statistical analysis that enable us to perform retrospective studies; (4) changes are easily incorporated because of the modular architecture; and (5) assessment of trial data collected at different sites is centralised to reduce statistical variance.

Doctoral theses in diagnostic imaging: a study of Spanish production between 1976 and 2011.

PubMed

Machan, K; Sendra Portero, F

2018-05-15

To analyze the production of doctoral theses in diagnostic imaging in Spain in the period comprising 1976 through 2011 with the aim of a) determining the number of theses and their distribution over time, b) describing the production in terms of universities and directors, and c) analyzing the content of the theses according to the imaging technique, anatomic site, and type of research used. The TESEO database was searched for "radiología" and/or "diagnóstico por imagen" and for terms related to diagnostic imaging in the title of the thesis. A total of 1036 theses related to diagnostic imaging were produced in 37 Spanish universities (mean, 29.6 theses/year; range, 4-59). A total of 963 thesis directors were identified; 10 of these supervised 10 or more theses. Most candidates and directors were men, although since the 2000-2001 academic year the number of male and female candidates has been similar. The anatomic regions most often included in diagnostic imaging theses were the abdomen (22.5%), musculoskeletal system (21.8%), central nervous system (16.4%), and neck and face (15.6%). The imaging techniques most often included were ultrasonography in the entire period (25.5%) and magnetic resonance imaging in the last 5 years. Most theses (63.8%) were related to clinical research. Despite certain limitations, the TESEO database makes it possible to analyze the production of doctoral theses in Spain effectively. The annual mean production of theses in diagnostic imaging is higher than in other medical specialties. This analysis reflects the historic evolution of imaging techniques and research in radiology as well as the development of Spanish universities. Copyright © 2018 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

Architecture and prototypical implementation of a semantic querying system for big Earth observation image bases

PubMed Central

Tiede, Dirk; Baraldi, Andrea; Sudmanns, Martin; Belgiu, Mariana; Lang, Stefan

2017-01-01

ABSTRACT Spatiotemporal analytics of multi-source Earth observation (EO) big data is a pre-condition for semantic content-based image retrieval (SCBIR). As a proof of concept, an innovative EO semantic querying (EO-SQ) subsystem was designed and prototypically implemented in series with an EO image understanding (EO-IU) subsystem. The EO-IU subsystem is automatically generating ESA Level 2 products (scene classification map, up to basic land cover units) from optical satellite data. The EO-SQ subsystem comprises a graphical user interface (GUI) and an array database embedded in a client server model. In the array database, all EO images are stored as a space-time data cube together with their Level 2 products generated by the EO-IU subsystem. The GUI allows users to (a) develop a conceptual world model based on a graphically supported query pipeline as a combination of spatial and temporal operators and/or standard algorithms and (b) create, save and share within the client-server architecture complex semantic queries/decision rules, suitable for SCBIR and/or spatiotemporal EO image analytics, consistent with the conceptual world model. PMID:29098143

Software for Displaying Data from Planetary Rovers

NASA Technical Reports Server (NTRS)

Powell, Mark; Backers, Paul; Norris, Jeffrey; Vona, Marsette; Steinke, Robert

2003-01-01

Science Activity Planner (SAP) DownlinkBrowser is a computer program that assists in the visualization of processed telemetric data [principally images, image cubes (that is, multispectral images), and spectra] that have been transmitted to Earth from exploratory robotic vehicles (rovers) on remote planets. It is undergoing adaptation to (1) the Field Integrated Design and Operations (FIDO) rover (a prototype Mars-exploration rover operated on Earth as a test bed) and (2) the Mars Exploration Rover (MER) mission. This program has evolved from its predecessor - the Web Interface for Telescience (WITS) software - and surpasses WITS in the processing, organization, and plotting of data. SAP DownlinkBrowser creates Extensible Markup Language (XML) files that organize data files, on the basis of content, into a sortable, searchable product database, without the overhead of a relational database. The data-display components of SAP DownlinkBrowser (descriptively named ImageView, 3DView, OrbitalView, PanoramaView, ImageCubeView, and SpectrumView) are designed to run in a memory footprint of at least 256MB on computers that utilize the Windows, Linux, and Solaris operating systems.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

A DBMS architecture for global change research

NASA Astrophysics Data System (ADS)

Hachem, Nabil I.; Gennert, Michael A.; Ward, Matthew O.

1993-08-01

The goal of this research is the design and development of an integrated system for the management of very large scientific databases, cartographic/geographic information processing, and exploratory scientific data analysis for global change research. The system will represent both spatial and temporal knowledge about natural and man-made entities on the eath's surface, following an object-oriented paradigm. A user will be able to derive, modify, and apply, procedures to perform operations on the data, including comparison, derivation, prediction, validation, and visualization. This work represents an effort to extend the database technology with an intrinsic class of operators, which is extensible and responds to the growing needs of scientific research. Of significance is the integration of many diverse forms of data into the database, including cartography, geography, hydrography, hypsography, images, and urban planning data. Equally important is the maintenance of metadata, that is, data about the data, such as coordinate transformation parameters, map scales, and audit trails of previous processing operations. This project will impact the fields of geographical information systems and global change research as well as the database community. It will provide an integrated database management testbed for scientific research, and a testbed for the development of analysis tools to understand and predict global change.

Constructing Benchmark Databases and Protocols for Medical Image Analysis: Diabetic Retinopathy

PubMed Central

Kauppi, Tomi; Kämäräinen, Joni-Kristian; Kalesnykiene, Valentina; Sorri, Iiris; Uusitalo, Hannu; Kälviäinen, Heikki

2013-01-01

We address the performance evaluation practices for developing medical image analysis methods, in particular, how to establish and share databases of medical images with verified ground truth and solid evaluation protocols. Such databases support the development of better algorithms, execution of profound method comparisons, and, consequently, technology transfer from research laboratories to clinical practice. For this purpose, we propose a framework consisting of reusable methods and tools for the laborious task of constructing a benchmark database. We provide a software tool for medical image annotation helping to collect class label, spatial span, and expert's confidence on lesions and a method to appropriately combine the manual segmentations from multiple experts. The tool and all necessary functionality for method evaluation are provided as public software packages. As a case study, we utilized the framework and tools to establish the DiaRetDB1 V2.1 database for benchmarking diabetic retinopathy detection algorithms. The database contains a set of retinal images, ground truth based on information from multiple experts, and a baseline algorithm for the detection of retinopathy lesions. PMID:23956787

Active browsing using similarity pyramids

NASA Astrophysics Data System (ADS)

Chen, Jau-Yuen; Bouman, Charles A.; Dalton, John C.

1998-12-01

In this paper, we describe a new approach to managing large image databases, which we call active browsing. Active browsing integrates relevance feedback into the browsing environment, so that users can modify the database's organization to suit the desired task. Our method is based on a similarity pyramid data structure, which hierarchically organizes the database, so that it can be efficiently browsed. At coarse levels, the similarity pyramid allows users to view the database as large clusters of similar images. Alternatively, users can 'zoom into' finer levels to view individual images. We discuss relevance feedback for the browsing process, and argue that it is fundamentally different from relevance feedback for more traditional search-by-query tasks. We propose two fundamental operations for active browsing: pruning and reorganization. Both of these operations depend on a user-defined relevance set, which represents the image or set of images desired by the user. We present statistical methods for accurately pruning the database, and we propose a new 'worm hole' distance metric for reorganizing the database, so that members of the relevance set are grouped together.

The EXOSAT database and archive

NASA Technical Reports Server (NTRS)

Reynolds, A. P.; Parmar, A. N.

1992-01-01

The EXOSAT database provides on-line access to the results and data products (spectra, images, and lightcurves) from the EXOSAT mission as well as access to data and logs from a number of other missions (such as EINSTEIN, COS-B, ROSAT, and IRAS). In addition, a number of familiar optical, infrared, and x ray catalogs, including the Hubble Space Telescope (HST) guide star catalog are available. The complete database is located at the EXOSAT observatory at ESTEC in the Netherlands and is accessible remotely via a captive account. The database management system was specifically developed to efficiently access the database and to allow the user to perform statistical studies on large samples of astronomical objects as well as to retrieve scientific and bibliographic information on single sources. The system was designed to be mission independent and includes timing, image processing, and spectral analysis packages as well as software to allow the easy transfer of analysis results and products to the user's own institute. The archive at ESTEC comprises a subset of the EXOSAT observations, stored on magnetic tape. Observations of particular interest were copied in compressed format to an optical jukebox, allowing users to retrieve and analyze selected raw data entirely from their terminals. Such analysis may be necessary if the user's needs are not accommodated by the products contained in the database (in terms of time resolution, spectral range, and the finesse of the background subtraction, for instance). Long-term archiving of the full final observation data is taking place at ESRIN in Italy as part of the ESIS program, again using optical media, and ESRIN have now assumed responsibility for distributing the data to the community. Tests showed that raw observational data (typically several tens of megabytes for a single target) can be transferred via the existing networks in reasonable time.

Correlation applied to the recognition of regular geometric figures

NASA Astrophysics Data System (ADS)

Lasso, William; Morales, Yaileth; Vega, Fabio; Díaz, Leonardo; Flórez, Daniel; Torres, Cesar

2013-11-01

It developed a system capable of recognizing of regular geometric figures, the images are taken by the software automatically through a process of validating the presence of figure to the camera lens, the digitized image is compared with a database that contains previously images captured, to subsequently be recognized and finally identified using sonorous words referring to the name of the figure identified. The contribution of system set out is the fact that the acquisition of data is done in real time and using a spy smart glasses with usb interface offering an system equally optimal but much more economical. This tool may be useful as a possible application for visually impaired people can get information of surrounding environment.

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.

Internet-based profiler system as integrative framework to support translational research

PubMed Central

Kim, Robert; Demichelis, Francesca; Tang, Jeffery; Riva, Alberto; Shen, Ronglai; Gibbs, Doug F; Mahavishno, Vasudeva; Chinnaiyan, Arul M; Rubin, Mark A

2005-01-01

Background Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions. Results The generic design of this system makes it compatible with multiple organ system (e.g., prostate, breast, lung, renal, and hematopoietic system,). Studies and folders are restricted to authorized users as required. Over the past 5 years, investigators at 2 academic institutions have scanned 656 TMA experiments and collected 63,311 digital images of these tissue samples. 68 pathologists from 12 major user groups have accessed the system. Two groups directly link clinical data from over 500 patients for immediate access and the remaining groups choose to maintain clinical and pathology data on separate systems. Profiler currently has 170 K data points such as staining intensity, tumor grade, and nuclear size. Due to the relational database structure, analysis can be easily performed on single or multiple TMA experimental results. The TMA module of Profiler can maintain images acquired from multiple systems. Conclusion We have developed a robust process to develop molecular biomarkers using TMA technology and an internet-based database system to track all steps of this process. This system is extendable to other types of molecular data as separate modules and is freely available to academic institutions for licensing. PMID:16364175

Internet-based Profiler system as integrative framework to support translational research.

PubMed

Kim, Robert; Demichelis, Francesca; Tang, Jeffery; Riva, Alberto; Shen, Ronglai; Gibbs, Doug F; Mahavishno, Vasudeva; Chinnaiyan, Arul M; Rubin, Mark A

2005-12-19

Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions. The generic design of this system makes it compatible with multiple organ system (e.g., prostate, breast, lung, renal, and hematopoietic system,). Studies and folders are restricted to authorized users as required. Over the past 5 years, investigators at 2 academic institutions have scanned 656 TMA experiments and collected 63,311 digital images of these tissue samples. 68 pathologists from 12 major user groups have accessed the system. Two groups directly link clinical data from over 500 patients for immediate access and the remaining groups choose to maintain clinical and pathology data on separate systems. Profiler currently has 170 K data points such as staining intensity, tumor grade, and nuclear size. Due to the relational database structure, analysis can be easily performed on single or multiple TMA experimental results. The TMA module of Profiler can maintain images acquired from multiple systems. We have developed a robust process to develop molecular biomarkers using TMA technology and an internet-based database system to track all steps of this process. This system is extendable to other types of molecular data as separate modules and is freely available to academic institutions for licensing.

Diamond Eye: a distributed architecture for image data mining

NASA Astrophysics Data System (ADS)

Burl, Michael C.; Fowlkes, Charless; Roden, Joe; Stechert, Andre; Mukhtar, Saleem

1999-02-01

Diamond Eye is a distributed software architecture, which enables users (scientists) to analyze large image collections by interacting with one or more custom data mining servers via a Java applet interface. Each server is coupled with an object-oriented database and a computational engine, such as a network of high-performance workstations. The database provides persistent storage and supports querying of the 'mined' information. The computational engine provides parallel execution of expensive image processing, object recognition, and query-by-content operations. Key benefits of the Diamond Eye architecture are: (1) the design promotes trial evaluation of advanced data mining and machine learning techniques by potential new users (all that is required is to point a web browser to the appropriate URL), (2) software infrastructure that is common across a range of science mining applications is factored out and reused, and (3) the system facilitates closer collaborations between algorithm developers and domain experts.

Database Technology Activities and Assessment for Defense Modeling and Simulation Office (DMSO) (August 1991-November 1992). A Documented Briefing

DTIC Science & Technology

1994-01-01

databases and identifying new data entities, data elements, and relationships . - Standard data naming conventions, schema, and definition processes...management system. The use of such a tool could offer: (1) structured support for representation of objects and their relationships to each other (and...their relationships to related multimedia objects such as an engineering drawing of the tank object or a satellite image that contains the installation

Implementation of an RBF neural network on embedded systems: real-time face tracking and identity verification.

PubMed

Yang, Fan; Paindavoine, M

2003-01-01

This paper describes a real time vision system that allows us to localize faces in video sequences and verify their identity. These processes are image processing techniques based on the radial basis function (RBF) neural network approach. The robustness of this system has been evaluated quantitatively on eight video sequences. We have adapted our model for an application of face recognition using the Olivetti Research Laboratory (ORL), Cambridge, UK, database so as to compare the performance against other systems. We also describe three hardware implementations of our model on embedded systems based on the field programmable gate array (FPGA), zero instruction set computer (ZISC) chips, and digital signal processor (DSP) TMS320C62, respectively. We analyze the algorithm complexity and present results of hardware implementations in terms of the resources used and processing speed. The success rates of face tracking and identity verification are 92% (FPGA), 85% (ZISC), and 98.2% (DSP), respectively. For the three embedded systems, the processing speeds for images size of 288 /spl times/ 352 are 14 images/s, 25 images/s, and 4.8 images/s, respectively.

The Einstein database of IPC x-ray observations of optically selected and radio-selected quasars, 1.

NASA Technical Reports Server (NTRS)

Wilkes, Belinda J.; Tananbaum, Harvey; Worrall, D. M.; Avni, Yoram; Oey, M. S.; Flanagan, Joan

1994-01-01

We present the first volume of the Einstein quasar database. The database includes estimates of the X-ray count rates, fluxes, and luminosities for 514 quasars and Seyfert 1 galaxies observed with the Imaging Proportional Counter (IPC) aboard the Einstein Observatory. All were previously known optically selected or radio-selected objects, and most were the targets of the X-ray observations. The X-ray properties of the Active Galactic Nuclei (AGNs) have been derived by reanalyzing the IPC data in a systematic manner to provide a uniform database for general use by the astronomical community. We use the database to extend earlier quasar luminosity studies which were made using only a subset of the currently available data. The database can be accessed on internet via the SAO Einstein on-line system ('Einline') and is available in ASCII format on magnetic tape and DOS diskette.

Deep Convolutional Neural Networks for breast cancer screening.

PubMed

Chougrad, Hiba; Zouaki, Hamid; Alheyane, Omar

2018-04-01

Radiologists often have a hard time classifying mammography mass lesions which leads to unnecessary breast biopsies to remove suspicions and this ends up adding exorbitant expenses to an already burdened patient and health care system. In this paper we developed a Computer-aided Diagnosis (CAD) system based on deep Convolutional Neural Networks (CNN) that aims to help the radiologist classify mammography mass lesions. Deep learning usually requires large datasets to train networks of a certain depth from scratch. Transfer learning is an effective method to deal with relatively small datasets as in the case of medical images, although it can be tricky as we can easily start overfitting. In this work, we explore the importance of transfer learning and we experimentally determine the best fine-tuning strategy to adopt when training a CNN model. We were able to successfully fine-tune some of the recent, most powerful CNNs and achieved better results compared to other state-of-the-art methods which classified the same public datasets. For instance we achieved 97.35% accuracy and 0.98 AUC on the DDSM database, 95.50% accuracy and 0.97 AUC on the INbreast database and 96.67% accuracy and 0.96 AUC on the BCDR database. Furthermore, after pre-processing and normalizing all the extracted Regions of Interest (ROIs) from the full mammograms, we merged all the datasets to build one large set of images and used it to fine-tune our CNNs. The CNN model which achieved the best results, a 98.94% accuracy, was used as a baseline to build the Breast Cancer Screening Framework. To evaluate the proposed CAD system and its efficiency to classify new images, we tested it on an independent database (MIAS) and got 98.23% accuracy and 0.99 AUC. The results obtained demonstrate that the proposed framework is performant and can indeed be used to predict if the mass lesions are benign or malignant. Copyright © 2018 Elsevier B.V. All rights reserved.

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

NASA Astrophysics Data System (ADS)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image. Experiments conducted on various popular face databases show promising performance of the proposed algorithm in varying lighting, expression, and partial occlusion conditions. Four databases were used for testing the performance of the proposed system: Yale Face database, Extended Yale Face database B, Japanese Female Facial Expression database, and CMU AMP Facial Expression database. The experimental results in all four databases show the effectiveness of the proposed system. Also, the computation cost is lower because of the simplified calculation steps. Research work is progressing to investigate the effectiveness of the proposed face recognition method on pose-varying conditions as well. It is envisaged that a multilane approach of trained frameworks at different pose bins and an appropriate voting strategy would lead to a good recognition rate in such situation.

Structured Forms Reference Set of Binary Images II (SFRS2)

National Institute of Standards and Technology Data Gateway

NIST Structured Forms Reference Set of Binary Images II (SFRS2) (Web, free access)   The second NIST database of structured forms (Special Database 6) consists of 5,595 pages of binary, black-and-white images of synthesized documents containing hand-print. The documents in this database are 12 different tax forms with the IRS 1040 Package X for the year 1988.

Low dose CT image restoration using a database of image patches

NASA Astrophysics Data System (ADS)

Ha, Sungsoo; Mueller, Klaus

2015-01-01

Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove the significant noise and streak artifacts in the reconstructed images. Most of these methods operate within the domain of the image that is subject to restoration. This, however, poses limitations on the extent of filtering possible. We advocate to take into consideration the vast body of external knowledge that exists in the domain of already acquired medical CT images, since after all, this is what radiologists do when they examine these low quality images. We can incorporate this knowledge by creating a database of prior scans, either of the same patient or a diverse corpus of different patients, to assist in the restoration process. Our paper follows up on our previous work that used a database of images. Using images, however, is challenging since it requires tedious and error prone registration and alignment. Our new method eliminates these problems by storing a diverse set of small image patches in conjunction with a localized similarity matching scheme. We also empirically show that it is sufficient to store these patches without anatomical tags since their statistics are sufficiently strong to yield good similarity matches from the database and as a direct effect, produce image restorations of high quality. A final experiment demonstrates that our global database approach can recover image features that are difficult to preserve with conventional denoising approaches.

ClearedLeavesDB: an online database of cleared plant leaf images

PubMed Central

2014-01-01

Background Leaf vein networks are critical to both the structure and function of leaves. A growing body of recent work has linked leaf vein network structure to the physiology, ecology and evolution of land plants. In the process, multiple institutions and individual researchers have assembled collections of cleared leaf specimens in which vascular bundles (veins) are rendered visible. In an effort to facilitate analysis and digitally preserve these specimens, high-resolution images are usually created, either of entire leaves or of magnified leaf subsections. In a few cases, collections of digital images of cleared leaves are available for use online. However, these collections do not share a common platform nor is there a means to digitally archive cleared leaf images held by individual researchers (in addition to those held by institutions). Hence, there is a growing need for a digital archive that enables online viewing, sharing and disseminating of cleared leaf image collections held by both institutions and individual researchers. Description The Cleared Leaf Image Database (ClearedLeavesDB), is an online web-based resource for a community of researchers to contribute, access and share cleared leaf images. ClearedLeavesDB leverages resources of large-scale, curated collections while enabling the aggregation of small-scale collections within the same online platform. ClearedLeavesDB is built on Drupal, an open source content management platform. It allows plant biologists to store leaf images online with corresponding meta-data, share image collections with a user community and discuss images and collections via a common forum. We provide tools to upload processed images and results to the database via a web services client application that can be downloaded from the database. Conclusions We developed ClearedLeavesDB, a database focusing on cleared leaf images that combines interactions between users and data via an intuitive web interface. The web interface allows storage of large collections and integrates with leaf image analysis applications via an open application programming interface (API). The open API allows uploading of processed images and other trait data to the database, further enabling distribution and documentation of analyzed data within the community. The initial database is seeded with nearly 19,000 cleared leaf images representing over 40 GB of image data. Extensible storage and growth of the database is ensured by using the data storage resources of the iPlant Discovery Environment. ClearedLeavesDB can be accessed at http://clearedleavesdb.org. PMID:24678985

ClearedLeavesDB: an online database of cleared plant leaf images.

PubMed

Das, Abhiram; Bucksch, Alexander; Price, Charles A; Weitz, Joshua S

2014-03-28

Leaf vein networks are critical to both the structure and function of leaves. A growing body of recent work has linked leaf vein network structure to the physiology, ecology and evolution of land plants. In the process, multiple institutions and individual researchers have assembled collections of cleared leaf specimens in which vascular bundles (veins) are rendered visible. In an effort to facilitate analysis and digitally preserve these specimens, high-resolution images are usually created, either of entire leaves or of magnified leaf subsections. In a few cases, collections of digital images of cleared leaves are available for use online. However, these collections do not share a common platform nor is there a means to digitally archive cleared leaf images held by individual researchers (in addition to those held by institutions). Hence, there is a growing need for a digital archive that enables online viewing, sharing and disseminating of cleared leaf image collections held by both institutions and individual researchers. The Cleared Leaf Image Database (ClearedLeavesDB), is an online web-based resource for a community of researchers to contribute, access and share cleared leaf images. ClearedLeavesDB leverages resources of large-scale, curated collections while enabling the aggregation of small-scale collections within the same online platform. ClearedLeavesDB is built on Drupal, an open source content management platform. It allows plant biologists to store leaf images online with corresponding meta-data, share image collections with a user community and discuss images and collections via a common forum. We provide tools to upload processed images and results to the database via a web services client application that can be downloaded from the database. We developed ClearedLeavesDB, a database focusing on cleared leaf images that combines interactions between users and data via an intuitive web interface. The web interface allows storage of large collections and integrates with leaf image analysis applications via an open application programming interface (API). The open API allows uploading of processed images and other trait data to the database, further enabling distribution and documentation of analyzed data within the community. The initial database is seeded with nearly 19,000 cleared leaf images representing over 40 GB of image data. Extensible storage and growth of the database is ensured by using the data storage resources of the iPlant Discovery Environment. ClearedLeavesDB can be accessed at http://clearedleavesdb.org.

Creation of a digital slide and tissue microarray resource from a multi-institutional predictive toxicology study in the rat: an initial report from the PredTox group.

PubMed

Mulrane, Laoighse; Rexhepaj, Elton; Smart, Valerie; Callanan, John J; Orhan, Diclehan; Eldem, Türkan; Mally, Angela; Schroeder, Susanne; Meyer, Kirstin; Wendt, Maria; O'Shea, Donal; Gallagher, William M

2008-08-01

The widespread use of digital slides has only recently come to the fore with the development of high-throughput scanners and high performance viewing software. This development, along with the optimisation of compression standards and image transfer techniques, has allowed the technology to be used in wide reaching applications including integration of images into hospital information systems and histopathological training, as well as the development of automated image analysis algorithms for prediction of histological aberrations and quantification of immunohistochemical stains. Here, the use of this technology in the creation of a comprehensive library of images of preclinical toxicological relevance is demonstrated. The images, acquired using the Aperio ScanScope CS and XT slide acquisition systems, form part of the ongoing EU FP6 Integrated Project, Innovative Medicines for Europe (InnoMed). In more detail, PredTox (abbreviation for Predictive Toxicology) is a subproject of InnoMed and comprises a consortium of 15 industrial (13 large pharma, 1 technology provider and 1 SME) and three academic partners. The primary aim of this consortium is to assess the value of combining data generated from 'omics technologies (proteomics, transcriptomics, metabolomics) with the results from more conventional toxicology methods, to facilitate further informed decision making in preclinical safety evaluation. A library of 1709 scanned images was created of full-face sections of liver and kidney tissue specimens from male Wistar rats treated with 16 proprietary and reference compounds of known toxicity; additional biological materials from these treated animals were separately used to create 'omics data, that will ultimately be used to populate an integrated toxicological database. In respect to assessment of the digital slides, a web-enabled digital slide management system, Digital SlideServer (DSS), was employed to enable integration of the digital slide content into the 'omics database and to facilitate remote viewing by pathologists connected with the project. DSS also facilitated manual annotation of digital slides by the pathologists, specifically in relation to marking particular lesions of interest. Tissue microarrays (TMAs) were constructed from the specimens for the purpose of creating a repository of tissue from animals used in the study with a view to later-stage biomarker assessment. As the PredTox consortium itself aims to identify new biomarkers of toxicity, these TMAs will be a valuable means of validation. In summary, a large repository of histological images was created enabling the subsequent pathological analysis of samples through remote viewing and, along with the utilisation of TMA technology, will allow the validation of biomarkers identified by the PredTox consortium. The population of the PredTox database with these digitised images represents the creation of the first toxicological database integrating 'omics and preclinical data with histological images.

Development of image and information management system for Korean standard brain

NASA Astrophysics Data System (ADS)

Chung, Soon Cheol; Choi, Do Young; Tack, Gye Rae; Sohn, Jin Hun

2004-04-01

The purpose of this study is to establish a reference for image acquisition for completing a standard brain for diverse Korean population, and to develop database management system that saves and manages acquired brain images and personal information of subjects. 3D MP-RAGE (Magnetization Prepared Rapid Gradient Echo) technique which has excellent Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) as well as reduces image acquisition time was selected for anatomical image acquisition, and parameter values were obtained for the optimal image acquisition. Using these standards, image data of 121 young adults (early twenties) were obtained and stored in the system. System was designed to obtain, save, and manage not only anatomical image data but also subjects' basic demographic factors, medical history, handedness inventory, state-trait anxiety inventory, A-type personality inventory, self-assessment depression inventory, mini-mental state examination, intelligence test, and results of personality test via a survey questionnaire. Additionally this system was designed to have functions of saving, inserting, deleting, searching, and printing image data and personal information of subjects, and to have accessibility to them as well as automatic connection setup with ODBC. This newly developed system may have major contribution to the completion of a standard brain for diverse Korean population since it can save and manage their image data and personal information.

An integrated one-step system to extract, analyze and annotate all relevant information from image-based cell screening of chemical libraries.

PubMed

Rabal, Obdulia; Link, Wolfgang; Serelde, Beatriz G; Bischoff, James R; Oyarzabal, Julen

2010-04-01

Here we report the development and validation of a complete solution to manage and analyze the data produced by image-based phenotypic screening campaigns of small-molecule libraries. In one step initial crude images are analyzed for multiple cytological features, statistical analysis is performed and molecules that produce the desired phenotypic profile are identified. A naïve Bayes classifier, integrating chemical and phenotypic spaces, is built and utilized during the process to assess those images initially classified as "fuzzy"-an automated iterative feedback tuning. Simultaneously, all this information is directly annotated in a relational database containing the chemical data. This novel fully automated method was validated by conducting a re-analysis of results from a high-content screening campaign involving 33 992 molecules used to identify inhibitors of the PI3K/Akt signaling pathway. Ninety-two percent of confirmed hits identified by the conventional multistep analysis method were identified using this integrated one-step system as well as 40 new hits, 14.9% of the total, originally false negatives. Ninety-six percent of true negatives were properly recognized too. A web-based access to the database, with customizable data retrieval and visualization tools, facilitates the posterior analysis of annotated cytological features which allows identification of additional phenotypic profiles; thus, further analysis of original crude images is not required.

Novel continuous authentication using biometrics

NASA Astrophysics Data System (ADS)

Dubey, Prakash; Patidar, Rinku; Mishra, Vikas; Norman, Jasmine; Mangayarkarasi, R.

2017-11-01

We explore whether a classifier can consistent1y verify c1ients and interact with the computer using camera and behavior of users. In this paper we propose a new way of authentication of user which wi1l capture many images of user in random time and ana1ysis of its touch biometric behavior. In this system experiment the touch conduct of a c1ient/user between an en1istment stage is stored in the database and it is checked its mean time behavior during equa1 partition of time. This touch behavior wi1l ab1e to accept or reject the user. This wi1l modify the use of biometric more accurate to use. In this system the work p1an going to perform is the user wi1l ask single time to a1low to take it picture before 1ogin. Then it wi1l take images of user without permission of user automatica1ly and store in the database. This images and existing image of user wi1l be compare and reject or accept wi1l depend on its comparison. The user touch behavior wi1l keep storing with number of touch make in equa1 amount of time of the user. This touch behavior and image wi1l fina1ly perform authentication of the user automatically.

Strategies for medical data extraction and presentation part 2: creating a customizable context and user-specific patient reference database.

PubMed

Reiner, Bruce

2015-06-01

One of the greatest challenges facing healthcare professionals is the ability to directly and efficiently access relevant data from the patient's healthcare record at the point of care; specific to both the context of the task being performed and the specific needs and preferences of the individual end-user. In radiology practice, the relative inefficiency of imaging data organization and manual workflow requirements serves as an impediment to historical imaging data review. At the same time, clinical data retrieval is even more problematic due to the quality and quantity of data recorded at the time of order entry, along with the relative lack of information system integration. One approach to address these data deficiencies is to create a multi-disciplinary patient referenceable database which consists of high-priority, actionable data within the cumulative patient healthcare record; in which predefined criteria are used to categorize and classify imaging and clinical data in accordance with anatomy, technology, pathology, and time. The population of this referenceable database can be performed through a combination of manual and automated methods, with an additional step of data verification introduced for data quality control. Once created, these referenceable databases can be filtered at the point of care to provide context and user-specific data specific to the task being performed and individual end-user requirements.

[LONI & Co: about the epistemic specificity of digital spaces of knowledge in cognitive neuroscience].

PubMed

Huber, Lara

2011-06-01

In the neurosciences digital databases more and more are becoming important tools of data rendering and distributing. This development is due to the growing impact of imaging based trial design in cognitive neuroscience, including morphological as much as functional imaging technologies. As the case of the 'Laboratory of Neuro Imaging' (LONI) is showing, databases are attributed a specific epistemological power: Since the 1990s databasing is seen to foster the integration of neuroscientific data, although local regimes of data production, -manipulation and--interpretation are also challenging this development. Databasing in the neurosciences goes along with the introduction of new structures of integrating local data, hence establishing digital spaces of knowledge (epistemic spaces): At this stage, inherent norms of digital databases are affecting regimes of imaging-based trial design, for example clinical research into Alzheimer's disease.

Ridge 2000 Data Management System

NASA Astrophysics Data System (ADS)

Goodwillie, A. M.; Carbotte, S. M.; Arko, R. A.; Haxby, W. F.; Ryan, W. B.; Chayes, D. N.; Lehnert, K. A.; Shank, T. M.

2005-12-01

Hosted at Lamont by the marine geoscience Data Management group, mgDMS, the NSF-funded Ridge 2000 electronic database, http://www.marine-geo.org/ridge2000/, is a key component of the Ridge 2000 multi-disciplinary program. The database covers each of the three Ridge 2000 Integrated Study Sites: Endeavour Segment, Lau Basin, and 8-11N Segment. It promotes the sharing of information to the broader community, facilitates integration of the suite of information collected at each study site, and enables comparisons between sites. The Ridge 2000 data system provides easy web access to a relational database that is built around a catalogue of cruise metadata. Any web browser can be used to perform a versatile text-based search which returns basic cruise and submersible dive information, sample and data inventories, navigation, and other relevant metadata such as shipboard personnel and links to NSF program awards. In addition, non-proprietary data files, images, and derived products which are hosted locally or in national repositories, as well as science and technical reports, can be freely downloaded. On the Ridge 2000 database page, our Data Link allows users to search the database using a broad range of parameters including data type, cruise ID, chief scientist, geographical location. The first Ridge 2000 field programs sailed in 2004 and, in addition to numerous data sets collected prior to the Ridge 2000 program, the database currently contains information on fifteen Ridge 2000-funded cruises and almost sixty Alvin dives. Track lines can be viewed using a recently- implemented Web Map Service button labelled Map View. The Ridge 2000 database is fully integrated with databases hosted by the mgDMS group for MARGINS and the Antarctic multibeam and seismic reflection data initiatives. Links are provided to partner databases including PetDB, SIOExplorer, and the ODP Janus system. Improved inter-operability with existing and new partner repositories continues to be strengthened. One major effort involves the gradual unification of the metadata across these partner databases. Standardised electronic metadata forms that can be filled in at sea are available from our web site. Interactive map-based exploration and visualisation of the Ridge 2000 database is provided by GeoMapApp, a freely-available Java(tm) application being developed within the mgDMS group. GeoMapApp includes high-resolution bathymetric grids for the 8-11N EPR segment and allows customised maps and grids for any of the Ridge 2000 ISS to be created. Vent and instrument locations can be plotted and saved as images, and Alvin dive photos are also available.

Establishment of a database of fetal congenital heart malformations and preliminary investigation of its clinical application.

PubMed

Gao, Jun-Xue; Pei, Qiu-Yan; Li, Yun-Tao; Yang, Zhen-Juan

2015-06-01

The aim of this study was to create a database of anatomical ultrathin cross-sectional images of fetal hearts with different congenital heart diseases (CHDs) and preliminarily to investigate its clinical application. Forty Chinese fetal heart samples from induced labor due to different CHDs were cut transversely at 60-μm thickness. All thoracic organs were removed from the thoracic cavity after formalin fixation, embedded in optimum cutting temperature compound, and then frozen at -25°C for 2 hours. Subsequently, macro shots of the frozen serial sections were obtained using a digital camera in order to build a database of anatomical ultrathin cross-sectional images. Images in the database clearly displayed the fetal heart structures. After importing the images into three-dimensional software, the following functions could be realized: (1) based on the original database of transverse sections, databases of sagittal and coronal sections could be constructed; and (2) the original and constructed databases could be displayed continuously and dynamically, and rotated in arbitrary angles. They could also be displayed synchronically. The aforementioned functions of the database allowed for the retrieval of images and three-dimensional anatomy characteristics of the different fetal CHDs, and virtualization of fetal echocardiography findings. A database of 40 different cross-sectional fetal CHDs was established. An extensive database library of fetal CHDs, from which sonographers and students can study the anatomical features of fetal CHDs and virtualize fetal echocardiography findings via either centralized training or distance education, can be established in the future by accumulating further cases. Copyright © 2015. Published by Elsevier B.V.

Securing palmprint authentication systems using spoof detection approach

NASA Astrophysics Data System (ADS)

Kanhangad, Vivek; Kumar, Abhishek

2013-12-01

Automated human authentication using features extracted from palmprint images has been studied extensively in the literature. Primary focus of the studies thus far has been the improvement of matching performance. As more biometric systems get deployed for wide range of applications, the threat of impostor attacks on these systems is on the rise. The most common among various types of attacks is the sensor level spoof attack using fake hands created using different materials. This paper investigates an approach for securing palmprint based biometric systems against spoof attacks that use photographs of the human hand for circumventing the system. The approach is based on the analysis of local texture patterns of acquired palmprint images for extracting discriminatory features. A trained binary classifier utilizes the discriminating information to determine if the input image is of real hand or a fake one. Experimental results, using 611 palmprint images corresponding to 100 subjects in the publicly available IITD palmprint image database, show that 1) palmprint authentication systems are highly vulnerable to spoof attacks and 2) the proposed spoof detection approach is effective for discriminating between real and fake image samples. In particular, the proposed approach achieves the best classification accuracy of 97.35%.

Compound image segmentation of published biomedical figures.

PubMed

Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

2018-04-01

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

Remote online monitoring and measuring system for civil engineering structures

NASA Astrophysics Data System (ADS)

Kujawińska, Malgorzata; Sitnik, Robert; Dymny, Grzegorz; Karaszewski, Maciej; Michoński, Kuba; Krzesłowski, Jakub; Mularczyk, Krzysztof; Bolewicki, Paweł

2009-06-01

In this paper a distributed intelligent system for civil engineering structures on-line measurement, remote monitoring, and data archiving is presented. The system consists of a set of optical, full-field displacement sensors connected to a controlling server. The server conducts measurements according to a list of scheduled tasks and stores the primary data or initial results in a remote centralized database. Simultaneously the server performs checks, ordered by the operator, which may in turn result with an alert or a specific action. The structure of whole system is analyzed along with the discussion on possible fields of application and the ways to provide a relevant security during data transport. Finally, a working implementation consisting of a fringe projection, geometrical moiré, digital image correlation and grating interferometry sensors and Oracle XE database is presented. The results from database utilized for on-line monitoring of a threshold value of strain for an exemplary area of interest at the engineering structure are presented and discussed.

DeitY-TU face database: its design, multiple camera capturing, characteristics, and evaluation

NASA Astrophysics Data System (ADS)

Bhowmik, Mrinal Kanti; Saha, Kankan; Saha, Priya; Bhattacharjee, Debotosh

2014-10-01

The development of the latest face databases is providing researchers different and realistic problems that play an important role in the development of efficient algorithms for solving the difficulties during automatic recognition of human faces. This paper presents the creation of a new visual face database, named the Department of Electronics and Information Technology-Tripura University (DeitY-TU) face database. It contains face images of 524 persons belonging to different nontribes and Mongolian tribes of north-east India, with their anthropometric measurements for identification. Database images are captured within a room with controlled variations in illumination, expression, and pose along with variability in age, gender, accessories, make-up, and partial occlusion. Each image contains the combined primary challenges of face recognition, i.e., illumination, expression, and pose. This database also represents some new features: soft biometric traits such as mole, freckle, scar, etc., and facial anthropometric variations that may be helpful for researchers for biometric recognition. It also gives an equivalent study of the existing two-dimensional face image databases. The database has been tested using two baseline algorithms: linear discriminant analysis and principal component analysis, which may be used by other researchers as the control algorithm performance score.

A case-oriented web-based training system for breast cancer diagnosis.

PubMed

Huang, Qinghua; Huang, Xianhai; Liu, Longzhong; Lin, Yidi; Long, Xingzhang; Li, Xuelong

2018-03-01

Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. We aim to provide a web-based breast ultrasound database for online training inexperienced radiologists and giving computer-assisted diagnostic information for detection and classification of the breast tumor. We introduce a web database which stores breast ultrasound images from breast cancer patients as well as their diagnostic information. A web-based training system using a feature scoring scheme based on Breast Imaging Reporting and Data System (BI-RADS) US lexicon was designed. A computer-aided diagnosis (CAD) subsystem was developed to assist the radiologists to make scores on the BI-RADS features for an input case. The training system possesses 1669 scored cases, where 412 cases are benign and 1257 cases are malignant. It was tested by 31 users including 12 interns, 11 junior radiologists, and 8 experienced senior radiologists. This online training system automatically creates case-based exercises to train and guide the newly employed or resident radiologists for the diagnosis of breast cancer using breast ultrasound images based on the BI-RADS. After the trainings, the interns and junior radiologists show significant improvement in the diagnosis of the breast tumor with ultrasound imaging (p-value < .05); meanwhile the senior radiologists show little improvement (p-value > .05). The online training system can improve the capabilities of early-career radiologists in distinguishing between the benign and malignant lesions and reduce the misdiagnosis of breast cancer in a quick, convenient and effective manner. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

A novel image database analysis system for maintenance of transportation facility : phase I.

DOT National Transportation Integrated Search

2010-06-01

Transportation is critical to the global economy and plays a particularly vital role in this regions economic growth. Transportation infrastructures such as highways, streets, and bridges represent one of the largest public investments of many gov...

apART: system for the acquisition, processing, archiving, and retrieval of digital images in an open, distributed imaging environment

NASA Astrophysics Data System (ADS)

Schneider, Uwe; Strack, Ruediger

1992-04-01

apART reflects the structure of an open, distributed environment. According to the general trend in the area of imaging, network-capable, general purpose workstations with capabilities of open system image communication and image input are used. Several heterogeneous components like CCD cameras, slide scanners, and image archives can be accessed. The system is driven by an object-oriented user interface where devices (image sources and destinations), operators (derived from a commercial image processing library), and images (of different data types) are managed and presented uniformly to the user. Browsing mechanisms are used to traverse devices, operators, and images. An audit trail mechanism is offered to record interactive operations on low-resolution image derivatives. These operations are processed off-line on the original image. Thus, the processing of extremely high-resolution raster images is possible, and the performance of resolution dependent operations is enhanced significantly during interaction. An object-oriented database system (APRIL), which can be browsed, is integrated into the system. Attribute retrieval is supported by the user interface. Other essential features of the system include: implementation on top of the X Window System (X11R4) and the OSF/Motif widget set; a SUN4 general purpose workstation, inclusive ethernet, magneto optical disc, etc., as the hardware platform for the user interface; complete graphical-interactive parametrization of all operators; support of different image interchange formats (GIF, TIFF, IIF, etc.); consideration of current IPI standard activities within ISO/IEC for further refinement and extensions.

Embedded wavelet-based face recognition under variable position

NASA Astrophysics Data System (ADS)

Cotret, Pascal; Chevobbe, Stéphane; Darouich, Mehdi

2015-02-01

For several years, face recognition has been a hot topic in the image processing field: this technique is applied in several domains such as CCTV, electronic devices delocking and so on. In this context, this work studies the efficiency of a wavelet-based face recognition method in terms of subject position robustness and performance on various systems. The use of wavelet transform has a limited impact on the position robustness of PCA-based face recognition. This work shows, for a well-known database (Yale face database B*), that subject position in a 3D space can vary up to 10% of the original ROI size without decreasing recognition rates. Face recognition is performed on approximation coefficients of the image wavelet transform: results are still satisfying after 3 levels of decomposition. Furthermore, face database size can be divided by a factor 64 (22K with K = 3). In the context of ultra-embedded vision systems, memory footprint is one of the key points to be addressed; that is the reason why compression techniques such as wavelet transform are interesting. Furthermore, it leads to a low-complexity face detection stage compliant with limited computation resources available on such systems. The approach described in this work is tested on three platforms from a standard x86-based computer towards nanocomputers such as RaspberryPi and SECO boards. For K = 3 and a database with 40 faces, the execution mean time for one frame is 0.64 ms on a x86-based computer, 9 ms on a SECO board and 26 ms on a RaspberryPi (B model).

SING: Subgraph search In Non-homogeneous Graphs

PubMed Central

2010-01-01

Background Finding the subgraphs of a graph database that are isomorphic to a given query graph has practical applications in several fields, from cheminformatics to image understanding. Since subgraph isomorphism is a computationally hard problem, indexing techniques have been intensively exploited to speed up the process. Such systems filter out those graphs which cannot contain the query, and apply a subgraph isomorphism algorithm to each residual candidate graph. The applicability of such systems is limited to databases of small graphs, because their filtering power degrades on large graphs. Results In this paper, SING (Subgraph search In Non-homogeneous Graphs), a novel indexing system able to cope with large graphs, is presented. The method uses the notion of feature, which can be a small subgraph, subtree or path. Each graph in the database is annotated with the set of all its features. The key point is to make use of feature locality information. This idea is used to both improve the filtering performance and speed up the subgraph isomorphism task. Conclusions Extensive tests on chemical compounds, biological networks and synthetic graphs show that the proposed system outperforms the most popular systems in query time over databases of medium and large graphs. Other specific tests show that the proposed system is effective for single large graphs. PMID:20170516

An Image Archive With The ACR/NEMA Message Formats

NASA Astrophysics Data System (ADS)

Seshadri, Sridhar B.; Khalsa, Satjeet; Arenson, Ronald L.; Brikman, Inna; Davey, Michael J.

1988-06-01

An image archive has been designed to manage and store radiologic images received from within the main Hospital and a from a suburban orthopedic clinic. Images are stored on both magnetic as well as optical media. Prior comparison examinations are combined with the current examination to generate a 'viewing folder' that is sent to the display station for primary diagnosis. An 'archive-manager' controls the database managment, periodic optical disk backup and 'viewing-folder' generation. Images are converted into the ACR/NEMA message format before being written to the optical disk. The software design of the 'archive-manager' and its associated modules is presented. Enhancements to the system are discussed.

Different approaches for the texture classification of a remote sensing image bank

NASA Astrophysics Data System (ADS)

Durand, Philippe; Brunet, Gerard; Ghorbanzadeh, Dariush; Jaupi, Luan

2018-04-01

In this paper, we summarize and compare two different approaches used by the authors, to classify different natural textures. The first approach, which is simple and inexpensive in computing time, uses a data bank image and an expert system able to classify different textures from a number of rules established by discipline specialists. The second method uses the same database and a neural networks approach.

Exploring Issues of Quality of Service in a Next Generation Internet Testbed: A Case Study Using PathMaster

PubMed Central

Shifman, Mark A.; Sayward, Frederick G.; Mattie, Mark E.; Miller, Perry L.

2002-01-01

This case study describes a project that explores issues of quality of service (QoS) relevant to the next-generation Internet (NGI), using the PathMaster application in a testbed environment. PathMaster is a prototype computer system that analyzes digitized cell images from cytology specimens and compares those images against an image database, returning a ranked set of “similar” cell images from the database. To perform NGI testbed evaluations, we used a cluster of nine parallel computation workstations configured as three subclusters using Cisco routers. This architecture provides a local “simulated Internet” in which we explored the following QoS strategies: (1) first-in-first-out queuing, (2) priority queuing, (3) weighted fair queuing, (4) weighted random early detection, and (5) traffic shaping. The study describes the results of using these strategies with a distributed version of the PathMaster system in the presence of different amounts of competing network traffic and discusses certain of the issues that arise. The goal of the study is to help introduce NGI QoS issues to the Medical Informatics community and to use the PathMaster NGI testbed to illustrate concretely certain of the QoS issues that arise. PMID:12223501

The Strabo digital data system for Structural Geology and Tectonics

NASA Astrophysics Data System (ADS)

Tikoff, Basil; Newman, Julie; Walker, J. Doug; Williams, Randy; Michels, Zach; Andrews, Joseph; Bunse, Emily; Ash, Jason; Good, Jessica

2017-04-01

We are developing the Strabo data system for the structural geology and tectonics community. The data system will allow researchers to share primary data, apply new types of analytical procedures (e.g., statistical analysis), facilitate interaction with other geology communities, and allow new types of science to be done. The data system is based on a graph database, rather than relational database approach, to increase flexibility and allow geologically realistic relationships between observations and measurements. Development is occurring on: 1) A field-based application that runs on iOS and Android mobile devices and can function in either internet connected or disconnected environments; and 2) A desktop system that runs only in connected settings and directly addresses the back-end database. The field application also makes extensive use of images, such as photos or sketches, which can be hierarchically arranged with encapsulated field measurements/observations across all scales. The system also accepts Shapefile, GEOJSON, KML formats made in ArcGIS and QGIS, and will allow export to these formats as well. Strabo uses two main concepts to organize the data: Spots and Tags. A Spot is any observation that characterizes a specific area. Below GPS resolution, a Spot can be tied to an image (outcrop photo, thin section, etc.). Spots are related in a purely spatial manner (one spot encloses anther spot, which encloses another, etc.). Tags provide a linkage between conceptually related spots. Together, this organization works seamlessly with the workflow of most geologists. We are expanding this effort to include microstructural data, as well as to the disciplines of sedimentology and petrology.

A self-organized learning strategy for object recognition by an embedded line of attraction

NASA Astrophysics Data System (ADS)

Seow, Ming-Jung; Alex, Ann T.; Asari, Vijayan K.

2012-04-01

For humans, a picture is worth a thousand words, but to a machine, it is just a seemingly random array of numbers. Although machines are very fast and efficient, they are vastly inferior to humans for everyday information processing. Algorithms that mimic the way the human brain computes and learns may be the solution. In this paper we present a theoretical model based on the observation that images of similar visual perceptions reside in a complex manifold in an image space. The perceived features are often highly structured and hidden in a complex set of relationships or high-dimensional abstractions. To model the pattern manifold, we present a novel learning algorithm using a recurrent neural network. The brain memorizes information using a dynamical system made of interconnected neurons. Retrieval of information is accomplished in an associative sense. It starts from an arbitrary state that might be an encoded representation of a visual image and converges to another state that is stable. The stable state is what the brain remembers. In designing a recurrent neural network, it is usually of prime importance to guarantee the convergence in the dynamics of the network. We propose to modify this picture: if the brain remembers by converging to the state representing familiar patterns, it should also diverge from such states when presented with an unknown encoded representation of a visual image belonging to a different category. That is, the identification of an instability mode is an indication that a presented pattern is far away from any stored pattern and therefore cannot be associated with current memories. These properties can be used to circumvent the plasticity-stability dilemma by using the fluctuating mode as an indicator to create new states. We capture this behavior using a novel neural architecture and learning algorithm, in which the system performs self-organization utilizing a stability mode and an instability mode for the dynamical system. Based on this observation we developed a self- organizing line attractor, which is capable of generating new lines in the feature space to learn unrecognized patterns. Experiments performed on UMIST pose database and CMU face expression variant database for face recognition have shown that the proposed nonlinear line attractor is able to successfully identify the individuals and it provided better recognition rate when compared to the state of the art face recognition techniques. Experiments on FRGC version 2 database has also provided excellent recognition rate in images captured in complex lighting environments. Experiments performed on the Japanese female face expression database and Essex Grimace database using the self organizing line attractor have also shown successful expression invariant face recognition. These results show that the proposed model is able to create nonlinear manifolds in a multidimensional feature space to distinguish complex patterns.

Automated collection of medical images for research from heterogeneous systems: trials and tribulations

NASA Astrophysics Data System (ADS)

Patel, M. N.; Looney, P.; Young, K.; Halling-Brown, M. D.

2014-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. Over the past two decades both diagnostic and therapeutic imaging have undergone a rapid growth, the ability to be able to harness this large influx of medical images can provide an essential resource for research and training. Traditionally, the systematic collection of medical images for research from heterogeneous sites has not been commonplace within the NHS and is fraught with challenges including; data acquisition, storage, secure transfer and correct anonymisation. Here, we describe a semi-automated system, which comprehensively oversees the collection of both unprocessed and processed medical images from acquisition to a centralised database. The provision of unprocessed images within our repository enables a multitude of potential research possibilities that utilise the images. Furthermore, we have developed systems and software to integrate these data with their associated clinical data and annotations providing a centralised dataset for research. Currently we regularly collect digital mammography images from two sites and partially collect from a further three, with efforts to expand into other modalities and sites currently ongoing. At present we have collected 34,014 2D images from 2623 individuals. In this paper we describe our medical image collection system for research and discuss the wide spectrum of challenges faced during the design and implementation of such systems.

Conversion of a traditional image archive into an image resource on compact disc.

PubMed Central

Andrew, S M; Benbow, E W

1997-01-01

The conversion of a traditional archive of pathology images was organised on 35 mm slides into a database of images stored on compact disc (CD-ROM), and textual descriptions were added to each image record. Students on a didactic pathology course found this resource useful as an aid to revision, despite relative computer illiteracy, and it is anticipated that students on a new problem based learning course, which incorporates experience with information technology, will benefit even more readily when they use the database as an educational resource. A text and image database on CD-ROM can be updated repeatedly, and the content manipulated to reflect the content and style of the courses it supports. Images PMID:9306931

A Kinect based sign language recognition system using spatio-temporal features

NASA Astrophysics Data System (ADS)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Early evaluation of MDIS workstations at Madigan Army Medical Center

NASA Astrophysics Data System (ADS)

Leckie, Robert G.; Goeringer, Fred; Smith, Donald V.; Bender, Gregory N.; Choi, Hyung-Sik; Haynor, David R.; Kim, Yongmin

1993-06-01

The image viewing workstation is an all-important link in the PACS (Picture Archiving and Communications System) chain since it represents the interface between the system and the user. For PACS to function, the working environment and transfer of information to the user must be the same or better than the traditional film-based system. The important characteristics of a workstation from a clinical standpoint are acceptable image quality, rapid response time, a friendly user interface, and a well-integrated, highly-reliable, fault-tolerant system which provides the user ample functions to complete his tasks successfully. Since early 1992, the MDIS (Medical Diagnostic Imaging Support) system's diagnostic and clinical workstations have been installed at Madigan Army Medical Center. Various functionalities and performance characteristics of the MDIS workstations such as image display, response time, database, and ergonomics will be presented. User comments and early experience with the workstations as well as new functionality recommended for the future will be discussed.

The application of use case modeling in designing medical imaging information systems.

PubMed

Safdari, Reza; Farzi, Jebraeil; Ghazisaeidi, Marjan; Mirzaee, Mahboobeh; Goodini, Azadeh

2013-01-01

Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control.

Performance and function of a high-speed multiple star topology image management system at Mayo Clinic Scottsdale.

PubMed

Pavlicek, W; Zavalkovskiy, B; Eversman, W G

1999-05-01

Mayo Clinic Scottsdale (MCS) is a busy outpatient facility (150,000 examinations per year) connected via asynchronous transfer mode (ATM; OC-3 155 MB/s) to a new Mayo Clinic Hospital (178 beds) located more than 12 miles distant. A primary care facility staffed by radiology lies roughly halfway between the hospital and clinic connected to both. Installed at each of the three locations is a high-speed star topology image network providing direct fiber connection (160 MB/s) from the local image storage unit (ISU) to the local radiology and clinical workstations. The clinic has 22 workstations in its star, the hospital has 13, and the primary care practice has two. In response to Mayo's request for a seamless service among the three locations, the vendor (GE Medical Systems, Milwaukee, WI) provided enhanced connectivity capability in a two-step process. First, a transfer gateway (TGW) was installed, tested, and implemented to provide the needed communication of the examinations generated at the three sites. Any examinations generated at either the hospital or the primary care facility (specified as the remote stars) automatically transfer their images to the ISU at the clinic. Permanent storage (Kodak optical jukebox, Rochester, NY) is only connected to the hub (Clinic) star. Thus, the hub ISU is provided with a copy of all examinations, while the two remote ISUs maintain local exams. Prefetching from the archive is intelligently accomplished during the off hours only to the hub star, thus providing the remote stars with network dependent access to comparison images. Image transfer is possible via remote log-on. The second step was the installation of an image transfer server (ITS) to replace the slower Digital Imaging and Communications in Medicine (DICOM)-based TGW, and a central higher performance database to replace the multiple database environment. This topology provides an enterprise view of the images at the three locations, while maintaining the high-speed performance of the local star connection to what is now called the short-term storage (STS). Performance was measured and 25 chest examinations (17 MB each) transferred in just over 4 minutes. Integration of the radiology information management system (RIMS) was modified to provide location-specific report and examination interfaces, thereby allowing local filtering of the worklist to remote and near real-time consultation, and remote examination monitoring of modalities are addressed with this technologic approach. The installation of the single database ITS environment has occurred for testing prior to implementation.

Image Engine: an object-oriented multimedia database for storing, retrieving and sharing medical images and text.

PubMed Central

Lowe, H. J.

1993-01-01

This paper describes Image Engine, an object-oriented, microcomputer-based, multimedia database designed to facilitate the storage and retrieval of digitized biomedical still images, video, and text using inexpensive desktop computers. The current prototype runs on Apple Macintosh computers and allows network database access via peer to peer file sharing protocols. Image Engine supports both free text and controlled vocabulary indexing of multimedia objects. The latter is implemented using the TView thesaurus model developed by the author. The current prototype of Image Engine uses the National Library of Medicine's Medical Subject Headings (MeSH) vocabulary (with UMLS Meta-1 extensions) as its indexing thesaurus. PMID:8130596

Human Visual System-Based Fundus Image Quality Assessment of Portable Fundus Camera Photographs.

PubMed

Wang, Shaoze; Jin, Kai; Lu, Haitong; Cheng, Chuming; Ye, Juan; Qian, Dahong

2016-04-01

Telemedicine and the medical "big data" era in ophthalmology highlight the use of non-mydriatic ocular fundus photography, which has given rise to indispensable applications of portable fundus cameras. However, in the case of portable fundus photography, non-mydriatic image quality is more vulnerable to distortions, such as uneven illumination, color distortion, blur, and low contrast. Such distortions are called generic quality distortions. This paper proposes an algorithm capable of selecting images of fair generic quality that would be especially useful to assist inexperienced individuals in collecting meaningful and interpretable data with consistency. The algorithm is based on three characteristics of the human visual system--multi-channel sensation, just noticeable blur, and the contrast sensitivity function to detect illumination and color distortion, blur, and low contrast distortion, respectively. A total of 536 retinal images, 280 from proprietary databases and 256 from public databases, were graded independently by one senior and two junior ophthalmologists, such that three partial measures of quality and generic overall quality were classified into two categories. Binary classification was implemented by the support vector machine and the decision tree, and receiver operating characteristic (ROC) curves were obtained and plotted to analyze the performance of the proposed algorithm. The experimental results revealed that the generic overall quality classification achieved a sensitivity of 87.45% at a specificity of 91.66%, with an area under the ROC curve of 0.9452, indicating the value of applying the algorithm, which is based on the human vision system, to assess the image quality of non-mydriatic photography, especially for low-cost ophthalmological telemedicine applications.

Fiber pixelated image database

NASA Astrophysics Data System (ADS)

Shinde, Anant; Perinchery, Sandeep Menon; Matham, Murukeshan Vadakke

2016-08-01

Imaging of physically inaccessible parts of the body such as the colon at micron-level resolution is highly important in diagnostic medical imaging. Though flexible endoscopes based on the imaging fiber bundle are used for such diagnostic procedures, their inherent honeycomb-like structure creates fiber pixelation effects. This impedes the observer from perceiving the information from an image captured and hinders the direct use of image processing and machine intelligence techniques on the recorded signal. Significant efforts have been made by researchers in the recent past in the development and implementation of pixelation removal techniques. However, researchers have often used their own set of images without making source data available which subdued their usage and adaptability universally. A database of pixelated images is the current requirement to meet the growing diagnostic needs in the healthcare arena. An innovative fiber pixelated image database is presented, which consists of pixelated images that are synthetically generated and experimentally acquired. Sample space encompasses test patterns of different scales, sizes, and shapes. It is envisaged that this proposed database will alleviate the current limitations associated with relevant research and development and would be of great help for researchers working on comb structure removal algorithms.

Establishment and maintenance of a standardized glioma tissue bank: Huashan experience.

PubMed

Aibaidula, Abudumijiti; Lu, Jun-feng; Wu, Jin-song; Zou, He-jian; Chen, Hong; Wang, Yu-qian; Qin, Zhi-yong; Yao, Yu; Gong, Ye; Che, Xiao-ming; Zhong, Ping; Li, Shi-qi; Bao, Wei-min; Mao, Ying; Zhou, Liang-fu

2015-06-01

Cerebral glioma is the most common brain tumor as well as one of the top ten malignant tumors in human beings. In spite of the great progress on chemotherapy and radiotherapy as well as the surgery strategies during the past decades, the mortality and morbidity are still high. One of the major challenges is to explore the pathogenesis and invasion of glioma at various "omics" levels (such as proteomics or genomics) and the clinical implications of biomarkers for diagnosis, prognosis or treatment of glioma patients. Establishment of a standardized tissue bank with high quality biospecimens annotated with clinical information is pivotal to the solution of these questions as well as the drug development process and translational research on glioma. Therefore, based on previous experience of tissue banks, standardized protocols for sample collection and storage were developed. We also developed two systems for glioma patient and sample management, a local database for medical records and a local image database for medical images. For future set-up of a regional biobank network in Shanghai, we also founded a centralized database for medical records. Hence we established a standardized glioma tissue bank with sufficient clinical data and medical images in Huashan Hospital. By September, 2013, tissues samples from 1,326 cases were collected. Histological diagnosis revealed that 73 % were astrocytic tumors, 17 % were oligodendroglial tumors, 2 % were oligoastrocytic tumors, 4 % were ependymal tumors and 4 % were other central nervous system neoplasms.

Ultra-low field nuclear magnetic resonance and magnetic resonance imaging to discriminate and identify materials

DOEpatents

Kraus, Robert H.; Matlashov, Andrei N.; Espy, Michelle A.; Volegov, Petr L.

2010-03-30

An ultra-low magnetic field NMR system can non-invasively examine containers. Database matching techniques can then identify hazardous materials within the containers. Ultra-low field NMR systems are ideal for this purpose because they do not require large powerful magnets and because they can examine materials enclosed in conductive shells such as lead shells. The NMR examination technique can be combined with ultra-low field NMR imaging, where an NMR image is obtained and analyzed to identify target volumes. Spatial sensitivity encoding can also be used to identify target volumes. After the target volumes are identified the NMR measurement technique can be used to identify their contents.

Astronomical Image Processing with Hadoop

NASA Astrophysics Data System (ADS)

Wiley, K.; Connolly, A.; Krughoff, S.; Gardner, J.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-07-01

In the coming decade astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. With a requirement that these images be analyzed in real time to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. In the commercial world, new techniques that utilize cloud computing have been developed to handle massive data streams. In this paper we describe how cloud computing, and in particular the map-reduce paradigm, can be used in astronomical data processing. We will focus on our experience implementing a scalable image-processing pipeline for the SDSS database using Hadoop (http://hadoop.apache.org). This multi-terabyte imaging dataset approximates future surveys such as those which will be conducted with the LSST. Our pipeline performs image coaddition in which multiple partially overlapping images are registered, integrated and stitched into a single overarching image. We will first present our initial implementation, then describe several critical optimizations that have enabled us to achieve high performance, and finally describe how we are incorporating a large in-house existing image processing library into our Hadoop system. The optimizations involve prefiltering of the input to remove irrelevant images from consideration, grouping individual FITS files into larger, more efficient indexed files, and a hybrid system in which a relational database is used to determine the input images relevant to the task. The incorporation of an existing image processing library, written in C++, presented difficult challenges since Hadoop is programmed primarily in Java. We will describe how we achieved this integration and the sophisticated image processing routines that were made feasible as a result. We will end by briefly describing the longer term goals of our work, namely detection and classification of transient objects and automated object classification.

NOAA Data Rescue of Key Solar Databases and Digitization of Historical Solar Images

NASA Astrophysics Data System (ADS)

Coffey, H. E.

2006-08-01

Over a number of years, the staff at NOAA National Geophysical Data Center (NGDC) has worked to rescue key solar databases by converting them to digital format and making them available via the World Wide Web. NOAA has had several data rescue programs where staff compete for funds to rescue important and critical historical data that are languishing in archives and at risk of being lost due to deteriorating condition, loss of any metadata or descriptive text that describe the databases, lack of interest or funding in maintaining databases, etc. The Solar-Terrestrial Physics Division at NGDC was able to obtain funds to key in some critical historical tabular databases. Recently the NOAA Climate Database Modernization Program (CDMP) funded a project to digitize historical solar images, producing a large online database of historical daily full disk solar images. The images include the wavelengths Calcium K, Hydrogen Alpha, and white light photos, as well as sunspot drawings and the comprehensive drawings of a multitude of solar phenomena on one daily map (Fraunhofer maps and Wendelstein drawings). Included in the digitization are high resolution solar H-alpha images taken at the Boulder Solar Observatory 1967-1984. The scanned daily images document many phases of solar activity, from decadal variation to rotational variation to daily changes. Smaller versions are available online. Larger versions are available by request. See http://www.ngdc.noaa.gov/stp/SOLAR/ftpsolarimages.html. The tabular listings and solar imagery will be discussed.

New Software for Ensemble Creation in the Spitzer-Space-Telescope Operations Database

NASA Technical Reports Server (NTRS)

Laher, Russ; Rector, John

2004-01-01

Some of the computer pipelines used to process digital astronomical images from NASA's Spitzer Space Telescope require multiple input images, in order to generate high-level science and calibration products. The images are grouped into ensembles according to well documented ensemble-creation rules by making explicit associations in the operations Informix database at the Spitzer Science Center (SSC). The advantage of this approach is that a simple database query can retrieve the required ensemble of pipeline input images. New and improved software for ensemble creation has been developed. The new software is much faster than the existing software because it uses pre-compiled database stored-procedures written in Informix SPL (SQL programming language). The new software is also more flexible because the ensemble creation rules are now stored in and read from newly defined database tables. This table-driven approach was implemented so that ensemble rules can be inserted, updated, or deleted without modifying software.

Internet (WWW) based system of ultrasonic image processing tools for remote image analysis.

PubMed

Zeng, Hong; Fei, Ding-Yu; Fu, Cai-Ting; Kraft, Kenneth A

2003-07-01

Ultrasonic Doppler color imaging can provide anatomic information and simultaneously render flow information within blood vessels for diagnostic purpose. Many researchers are currently developing ultrasound image processing algorithms in order to provide physicians with accurate clinical parameters from the images. Because researchers use a variety of computer languages and work on different computer platforms to implement their algorithms, it is difficult for other researchers and physicians to access those programs. A system has been developed using World Wide Web (WWW) technologies and HTTP communication protocols to publish our ultrasonic Angle Independent Doppler Color Image (AIDCI) processing algorithm and several general measurement tools on the Internet, where authorized researchers and physicians can easily access the program using web browsers to carry out remote analysis of their local ultrasonic images or images provided from the database. In order to overcome potential incompatibility between programs and users' computer platforms, ActiveX technology was used in this project. The technique developed may also be used for other research fields.

Point spread function engineering for iris recognition system design.

PubMed

Ashok, Amit; Neifeld, Mark A

2010-04-01

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

[A new concept for integration of image databanks into a comprehensive patient documentation].

PubMed

Schöll, E; Holm, J; Eggli, S

2001-05-01

Image processing and archiving are of increasing importance in the practice of modern medicine. Particularly due to the introduction of computer-based investigation methods, physicians are dealing with a wide variety of analogue and digital picture archives. On the other hand, clinical information is stored in various text-based information systems without integration of image components. The link between such traditional medical databases and picture archives is a prerequisite for efficient data management as well as for continuous quality control and medical education. At the Department of Orthopedic Surgery, University of Berne, a software program was developed to create a complete multimedia electronic patient record. The client-server system contains all patients' data, questionnaire-based quality control, and a digital picture archive. Different interfaces guarantee the integration into the hospital's data network. This article describes our experiences in the development and introduction of a comprehensive image archiving system at a large orthopedic center.

IMAGES: An IMage Archive Generated for Exoplanet Surveys

NASA Astrophysics Data System (ADS)

Tanner, A.

2010-10-01

In the past few years, there have been a menagerie of high contrast imaging surveys which have resulted in the detection of the first brown dwarfs orbiting main sequence stars and the first directly imaged exo-planetary systems. While these discoveries are scientifically rewarding, they are rare and the majority of the images collected during these surveys show single target stars. In addition, while papers will report the number of companion non-detections down to a sensitivity limit at a specific distance from the star, the corresponding images are rarely made available to the public. To date, such data exists for over a thousand stars. Thus, we are creating IMAGES, the IMage Archive Generated for Exoplanet Searches, as a repository for high contrast images gathered from published direct imaging sub-stellar and exoplanet companion surveys. This database will serve many purposes such as 1) facilitating common proper motion confirmation for candidate companions, 2) reducing the number of redundant observations of non-detection fields, 3) providing multiplicity precursor information to better select targets for future exoplanet missions, 4) providing stringent limits on the companion fraction of stars for a wide range of age, spectral type and star formation environment, and 5) provide multi-epoch images of stars with known companions for orbital monitoring. This database will be open to the public and will be searchable and sortable and will be extremely useful for future direct imaging programs such as GPI and SPHERE as well as future planet search programs such as JWST and SIM.

Smartphone-coupled rhinolaryngoscopy at the point of care

NASA Astrophysics Data System (ADS)

Mink, Jonah; Bolton, Frank J.; Sebag, Cathy M.; Peterson, Curtis W.; Assia, Shai; Levitz, David

2018-02-01

Rhinolaryngoscopy remains difficult to perform in resource-limited settings due to the high cost of purchasing and maintaining equipment as well as the need for specialists to interpret exam findings. While the lack of expertise can be obviated by adopting telemedicine-based approaches, the capture, storage, and sharing of images/video is not a common native functionality of medical devices. Most rhinolaryngoscopy systems consist of an endoscope that interfaces with the patient's naso/oropharynx, and a tower of modules that record video/images. However, these expensive and bulky modules can be replaced by a smartphone that can fulfill the same functions but at a lower cost. To demonstrate this, a commercially available rhinolaryngoscope was coupled to a smartphone using a 3D-printed adapter. Software developed for other clinical applications was repurposed for ENT use, including an application that controls image and video capture, a HIPAA-compliant image/video storage and transfer cloud database, and customized software features developed to improve practitioner competency. Audio recording capabilities to assess speech pathology were also integrated into the smartphone rhinolaryngoscope system. The illumination module coupled onto the endoscope remained unchanged. The spatial resolution of the rhinolaryngoscope system was defined by the fiber diameter of endoscope fiber bundle, rather than the smartphone camera. The mobile rhinolaryngoscope system was used with appropriate patients by a general practitioner in an office setting. The general practitioner then consulted with an ENT specialist via the HIPAA compliant cloud database and workflow modules on difficult cases. These results suggest the smartphone-based rhinolaryngoscope holds promise for use in low-resource settings.

Retina Image Analysis and Ocular Telehealth: The Oak Ridge National Laboratory-Hamilton Eye Institute Case Study

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

Karnowski, Thomas Paul; Giancardo, Luca; Li, Yaquin

2013-01-01

Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to howmore » validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.« less

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

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.

Discriminative Projection Selection Based Face Image Hashing

NASA Astrophysics Data System (ADS)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Glacier Land Ice Measurements from Space (GLIMS) and the GLIMS Information Management System at NSIDC

NASA Astrophysics Data System (ADS)

Machado, A. E.; Scharfen, G. R.; Barry, R. G.; Khalsa, S. S.; Raup, B.; Swick, R.; Troisi, V. J.; Wang, I.

2001-12-01

GLIMS (Global Land Ice Measurements from Space) is an international project to survey a majority of the world's glaciers with the accuracy and precision needed to assess recent changes and determine trends in glacial environments. This will be accomplished by: comprehensive periodic satellite measurements, coordinated distribution of screened image data, analysis of images at worldwide Regional Centers, validation of analyses, and a publicly accessible database. The primary data source will be from the ASTER (Advanced Spaceborne Thermal Emission and reflection Radiometer) instrument aboard the EOS Terra spacecraft, and Landsat ETM+ (Enhanced Thematic Mapper Plus), currently in operation. Approximately 700 ASTER images have been acquired with GLIMS gain settings as of mid-2001. GLIMS is a collaborative effort with the United States Geological Survey (USGS), the National Aeronautics Space Adminstration (NASA), other U.S. Federal Agencies and a group of internationally distributed glaciologists at Regional Centers of expertise. The National Snow and Ice Data Center (NSIDC) is developing the information management system for GLIMS. We will ingest and maintain GLIMS-analyzed glacier data from Regional Centers and provide access to the data via the World Wide Web. The GLIMS database will include measurements (over time) of glacier length, area, boundaries, topography, surface velocity vectors, and snowline elevation, derived primarily from remote sensing data. The GLIMS information management system at NSIDC will provide an easy to use and widely accessible service for the glaciological community and other users needing information about the world's glaciers. The structure of the international GLIMS consortium, status of database development, sample imagery and derived analyses and user search and order interfaces will be demonstrated. More information on GLIMS is available at: http://www.glims.org/.

Gender classification system in uncontrolled environments

NASA Astrophysics Data System (ADS)

Zeng, Pingping; Zhang, Yu-Jin; Duan, Fei

2011-01-01

Most face analysis systems available today perform mainly on restricted databases of images in terms of size, age, illumination. In addition, it is frequently assumed that all images are frontal and unconcealed. Actually, in a non-guided real-time supervision, the face pictures taken may often be partially covered and with head rotation less or more. In this paper, a special system supposed to be used in real-time surveillance with un-calibrated camera and non-guided photography is described. It mainly consists of five parts: face detection, non-face filtering, best-angle face selection, texture normalization, and gender classification. Emphases are focused on non-face filtering and best-angle face selection parts as well as texture normalization. Best-angle faces are figured out by PCA reconstruction, which equals to an implicit face alignment and results in a huge increase of the accuracy for gender classification. Dynamic skin model and a masked PCA reconstruction algorithm are applied to filter out faces detected in error. In order to fully include facial-texture and shape-outline features, a hybrid feature that is a combination of Gabor wavelet and PHoG (pyramid histogram of gradients) was proposed to equitable inner texture and outer contour. Comparative study on the effects of different non-face filtering and texture masking methods in the context of gender classification by SVM is reported through experiments on a set of UT (a company name) face images, a large number of internet images and CAS (Chinese Academy of Sciences) face database. Some encouraging results are obtained.

The HST/WFC3 Quicklook Project: A User Interface to Hubble Space Telescope Wide Field Camera 3 Data

NASA Astrophysics Data System (ADS)

Bourque, Matthew; Bajaj, Varun; Bowers, Ariel; Dulude, Michael; Durbin, Meredith; Gosmeyer, Catherine; Gunning, Heather; Khandrika, Harish; Martlin, Catherine; Sunnquist, Ben; Viana, Alex

2017-06-01

The Hubble Space Telescope's Wide Field Camera 3 (WFC3) instrument, comprised of two detectors, UVIS (Ultraviolet-Visible) and IR (Infrared), has been acquiring ~ 50-100 images daily since its installation in 2009. The WFC3 Quicklook project provides a means for instrument analysts to store, calibrate, monitor, and interact with these data through the various Quicklook systems: (1) a ~ 175 TB filesystem, which stores the entire WFC3 archive on disk, (2) a MySQL database, which stores image header data, (3) a Python-based automation platform, which currently executes 22 unique calibration/monitoring scripts, (4) a Python-based code library, which provides system functionality such as logging, downloading tools, database connection objects, and filesystem management, and (5) a Python/Flask-based web interface to the Quicklook system. The Quicklook project has enabled large-scale WFC3 analyses and calibrations, such as the monitoring of the health and stability of the WFC3 instrument, the measurement of ~ 20 million WFC3/UVIS Point Spread Functions (PSFs), the creation of WFC3/IR persistence calibration products, and many others.

RAPTOR-scan: Identifying and Tracking Objects Through Thousands of Sky Images

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

Davidoff, Sherri; Wozniak, Przemyslaw

2004-09-28

The RAPTOR-scan system mines data for optical transients associated with gamma-ray bursts and is used to create a catalog for the RAPTOR telescope system. RAPTOR-scan can detect and track individual astronomical objects across data sets containing millions of observed points.Accurately identifying a real object over many optical images (clustering the individual appearances) is necessary in order to analyze object light curves. To achieve this, RAPTOR telescope observations are sent in real time to a database. Each morning, a program based on the DBSCAN algorithm clusters the observations and labels each one with an object identifier. Once clustering is complete, themore » analysis program may be used to query the database and produce light curves, maps of the sky field, or other informative displays.Although RAPTOR-scan was designed for the RAPTOR optical telescope system, it is a general tool designed to identify objects in a collection of astronomical data and facilitate quick data analysis. RAPTOR-scan will be released as free software under the GNU General Public License.« less

Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium.

PubMed

Dodd, Lori E; Wagner, Robert F; Armato, Samuel G; McNitt-Gray, Michael F; Beiden, Sergey; Chan, Heang-Ping; Gur, David; McLennan, Geoffrey; Metz, Charles E; Petrick, Nicholas; Sahiner, Berkman; Sayre, Jim

2004-04-01

Cancer of the lung and bronchus is the leading fatal malignancy in the United States. Five-year survival is low, but treatment of early stage disease considerably improves chances of survival. Advances in multidetector-row computed tomography technology provide detection of smaller lung nodules and offer a potentially effective screening tool. The large number of images per exam, however, requires considerable radiologist time for interpretation and is an impediment to clinical throughput. Thus, computer-aided diagnosis (CAD) methods are needed to assist radiologists with their decision making. To promote the development of CAD methods, the National Cancer Institute formed the Lung Image Database Consortium (LIDC). The LIDC is charged with developing the consensus and standards necessary to create an image database of multidetector-row computed tomography lung images as a resource for CAD researchers. To develop such a prospective database, its potential uses must be anticipated. The ultimate applications will influence the information that must be included along with the images, the relevant measures of algorithm performance, and the number of required images. In this article we outline assessment methodologies and statistical issues as they relate to several potential uses of the LIDC database. We review methods for performance assessment and discuss issues of defining "truth" as well as the complications that arise when truth information is not available. We also discuss issues about sizing and populating a database.

Perceptual quality prediction on authentically distorted images using a bag of features approach

PubMed Central

Ghadiyaram, Deepti; Bovik, Alan C.

2017-01-01

Current top-performing blind perceptual image quality prediction models are generally trained on legacy databases of human quality opinion scores on synthetically distorted images. Therefore, they learn image features that effectively predict human visual quality judgments of inauthentic and usually isolated (single) distortions. However, real-world images usually contain complex composite mixtures of multiple distortions. We study the perceptually relevant natural scene statistics of such authentically distorted images in different color spaces and transform domains. We propose a “bag of feature maps” approach that avoids assumptions about the type of distortion(s) contained in an image and instead focuses on capturing consistencies—or departures therefrom—of the statistics of real-world images. Using a large database of authentically distorted images, human opinions of them, and bags of features computed on them, we train a regressor to conduct image quality prediction. We demonstrate the competence of the features toward improving automatic perceptual quality prediction by testing a learned algorithm using them on a benchmark legacy database as well as on a newly introduced distortion-realistic resource called the LIVE In the Wild Image Quality Challenge Database. We extensively evaluate the perceptual quality prediction model and algorithm and show that it is able to achieve good-quality prediction power that is better than other leading models. PMID:28129417

Implementation of an anonymisation tool for clinical trials using a clinical trial processor integrated with an existing trial patient data information system.

PubMed

Aryanto, Kadek Y E; Broekema, André; Oudkerk, Matthijs; van Ooijen, Peter M A

2012-01-01

To present an adapted Clinical Trial Processor (CTP) test set-up for receiving, anonymising and saving Digital Imaging and Communications in Medicine (DICOM) data using external input from the original database of an existing clinical study information system to guide the anonymisation process. Two methods are presented for an adapted CTP test set-up. In the first method, images are pushed from the Picture Archiving and Communication System (PACS) using the DICOM protocol through a local network. In the second method, images are transferred through the internet using the HTTPS protocol. In total 25,000 images from 50 patients were moved from the PACS, anonymised and stored within roughly 2 h using the first method. In the second method, an average of 10 images per minute were transferred and processed over a residential connection. In both methods, no duplicated images were stored when previous images were retransferred. The anonymised images are stored in appropriate directories. The CTP can transfer and process DICOM images correctly in a very easy set-up providing a fast, secure and stable environment. The adapted CTP allows easy integration into an environment in which patient data are already included in an existing information system.

An information gathering system for medical image inspection

NASA Astrophysics Data System (ADS)

Lee, Young-Jin; Bajcsy, Peter

2005-04-01

We present an information gathering system for medical image inspection that consists of software tools for capturing computer-centric and human-centric information. Computer-centric information includes (1) static annotations, such as (a) image drawings enclosing any selected area, a set of areas with similar colors, a set of salient points, and (b) textual descriptions associated with either image drawings or links between pairs of image drawings, and (2) dynamic (or temporal) information, such as mouse movements, zoom level changes, image panning and frame selections from an image stack. Human-centric information is represented by video and audio signals that are acquired by computer-mounted cameras and microphones. The short-term goal of the presented system is to facilitate learning of medical novices from medical experts, while the long-term goal is to data mine all information about image inspection for assisting in making diagnoses. In this work, we built basic software functionality for gathering computer-centric and human-centric information of the aforementioned variables. Next, we developed the information playback capabilities of all gathered information for educational purposes. Finally, we prototyped text-based and image template-based search engines to retrieve information from recorded annotations, for example, (a) find all annotations containing the word "blood vessels", or (b) search for similar areas to a selected image area. The information gathering system for medical image inspection reported here has been tested with images from the Histology Atlas database.

Segmentation method of eye region based on fuzzy logic system for classifying open and closed eyes

NASA Astrophysics Data System (ADS)

Kim, Ki Wan; Lee, Won Oh; Kim, Yeong Gon; Hong, Hyung Gil; Lee, Eui Chul; Park, Kang Ryoung

2015-03-01

The classification of eye openness and closure has been researched in various fields, e.g., driver drowsiness detection, physiological status analysis, and eye fatigue measurement. For a classification with high accuracy, accurate segmentation of the eye region is required. Most previous research used the segmentation method by image binarization on the basis that the eyeball is darker than skin, but the performance of this approach is frequently affected by thick eyelashes or shadows around the eye. Thus, we propose a fuzzy-based method for classifying eye openness and closure. First, the proposed method uses I and K color information from the HSI and CMYK color spaces, respectively, for eye segmentation. Second, the eye region is binarized using the fuzzy logic system based on I and K inputs, which is less affected by eyelashes and shadows around the eye. The combined image of I and K pixels is obtained through the fuzzy logic system. Third, in order to reflect the effect by all the inference values on calculating the output score of the fuzzy system, we use the revised weighted average method, where all the rectangular regions by all the inference values are considered for calculating the output score. Fourth, the classification of eye openness or closure is successfully made by the proposed fuzzy-based method with eye images of low resolution which are captured in the environment of people watching TV at a distance. By using the fuzzy logic system, our method does not require the additional procedure of training irrespective of the chosen database. Experimental results with two databases of eye images show that our method is superior to previous approaches.

[Research and development of medical case database: a novel medical case information system integrating with biospecimen management].

PubMed

Pan, Shiyang; Mu, Yuan; Wang, Hong; Wang, Tong; Huang, Peijun; Ma, Jianfeng; Jiang, Li; Zhang, Jie; Gu, Bing; Yi, Lujiang

2010-04-01

To meet the needs of management of medical case information and biospecimen simultaneously, we developed a novel medical case information system integrating with biospecimen management. The database established by MS SQL Server 2000 covered, basic information, clinical diagnosis, imaging diagnosis, pathological diagnosis and clinical treatment of patient; physicochemical property, inventory management and laboratory analysis of biospecimen; users log and data maintenance. The client application developed by Visual C++ 6.0 was used to implement medical case and biospecimen management, which was based on Client/Server model. This system can perform input, browse, inquest, summary of case and related biospecimen information, and can automatically synthesize case-records based on the database. Management of not only a long-term follow-up on individual, but also of grouped cases organized according to the aim of research can be achieved by the system. This system can improve the efficiency and quality of clinical researches while biospecimens are used coordinately. It realizes synthesized and dynamic management of medical case and biospecimen, which may be considered as a new management platform.

Building structural similarity database for metric learning

NASA Astrophysics Data System (ADS)

Jin, Guoxin; Pappas, Thrasyvoulos N.

2015-03-01

We propose a new approach for constructing databases for training and testing similarity metrics for structurally lossless image compression. Our focus is on structural texture similarity (STSIM) metrics and the matched-texture compression (MTC) approach. We first discuss the metric requirements for structurally lossless compression, which differ from those of other applications such as image retrieval, classification, and understanding. We identify "interchangeability" as the key requirement for metric performance, and partition the domain of "identical" textures into three regions, of "highest," "high," and "good" similarity. We design two subjective tests for data collection, the first relies on ViSiProG to build a database of "identical" clusters, and the second builds a database of image pairs with the "highest," "high," "good," and "bad" similarity labels. The data for the subjective tests is generated during the MTC encoding process, and consist of pairs of candidate and target image blocks. The context of the surrounding image is critical for training the metrics to detect lighting discontinuities, spatial misalignments, and other border artifacts that have a noticeable effect on perceptual quality. The identical texture clusters are then used for training and testing two STSIM metrics. The labelled image pair database will be used in future research.

Major Automated Information Systems: Selected Defense Programs Need to Implement Key Acquisition Practices

DTIC Science & Technology

2014-03-01

ledger accounting, payroll , and supply chain management. 4During our review, one of these programs—Air Force’s Air and Space Operations Center- Weapon...intended to provide an Army tactical biometric collection capability to capture an adversary or neutral person’s biometric data (e.g., fingerprint, iris...image, and facial image) and enroll them into DOD’s enterprise authoritative biometric database to positively identify and verify the identity of

Geodemographic segmentation systems for screening health data.

PubMed Central

Openshaw, S; Blake, M

1995-01-01

AIM--To describe how geodemographic segmentation systems might be useful as a quick and easy way of exploring postcoded health databases for potential interesting patterns related to deprivation and other socioeconomic characteristics. DESIGN AND SETTING--This is demonstrated using GB Profiles, a freely available geodemographic classification system developed at Leeds University. It is used here to screen a database of colorectal cancer registrations as a first step in the analysis of that data. RESULTS AND CONCLUSION--Conventional geodemographics is a fairly simple technology and a number of outstanding methodological problems are identified. A solution to some problems is illustrated by using neural net based classifiers and then by reference to a more sophisticated geodemographic approach via a data optimal segmentation technique. Images PMID:8594132

A network-based training environment: a medical image processing paradigm.

PubMed

Costaridou, L; Panayiotakis, G; Sakellaropoulos, P; Cavouras, D; Dimopoulos, J

1998-01-01

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

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

PubMed

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

1998-03-01

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

The Nencki Affective Picture System (NAPS): introduction to a novel, standardized, wide-range, high-quality, realistic picture database.

PubMed

Marchewka, Artur; Zurawski, Łukasz; Jednoróg, Katarzyna; Grabowska, Anna

2014-06-01

Selecting appropriate stimuli to induce emotional states is essential in affective research. Only a few standardized affective stimulus databases have been created for auditory, language, and visual materials. Numerous studies have extensively employed these databases using both behavioral and neuroimaging methods. However, some limitations of the existing databases have recently been reported, including limited numbers of stimuli in specific categories or poor picture quality of the visual stimuli. In the present article, we introduce the Nencki Affective Picture System (NAPS), which consists of 1,356 realistic, high-quality photographs that are divided into five categories (people, faces, animals, objects, and landscapes). Affective ratings were collected from 204 mostly European participants. The pictures were rated according to the valence, arousal, and approach-avoidance dimensions using computerized bipolar semantic slider scales. Normative ratings for the categories are presented for each dimension. Validation of the ratings was obtained by comparing them to ratings generated using the Self-Assessment Manikin and the International Affective Picture System. In addition, the physical properties of the photographs are reported, including luminance, contrast, and entropy. The new database, with accompanying ratings and image parameters, allows researchers to select a variety of visual stimulus materials specific to their experimental questions of interest. The NAPS system is freely accessible to the scientific community for noncommercial use by request at http://naps.nencki.gov.pl .

The development of digital library system for drug research information.

PubMed

Kim, H J; Kim, S R; Yoo, D S; Lee, S H; Suh, O K; Cho, J H; Shin, H T; Yoon, J P

1998-01-01

The sophistication of computer technology and information transmission on internet has made various cyber information repository available to information consumers. In the era of information super-highway, the digital library which can be accessed from remote sites at any time is considered the prototype of information repository. Using object-oriented DBMS, the very first model of digital library for pharmaceutical researchers and related professionals in Korea has been developed. The published research papers and researchers' personal information was included in the database. For database with research papers, 13 domestic journals were abstracted and scanned for full-text image files which can be viewed by Internet web browsers. The database with researchers' personal information was also developed and interlinked to the database with research papers. These database will be continuously updated and will be combined with world-wide information as the unique digital library in the field of pharmacy.

Palmprint and face score level fusion: hardware implementation of a contactless small sample biometric system

NASA Astrophysics Data System (ADS)

Poinsot, Audrey; Yang, Fan; Brost, Vincent

2011-02-01

Including multiple sources of information in personal identity recognition and verification gives the opportunity to greatly improve performance. We propose a contactless biometric system that combines two modalities: palmprint and face. Hardware implementations are proposed on the Texas Instrument Digital Signal Processor and Xilinx Field-Programmable Gate Array (FPGA) platforms. The algorithmic chain consists of a preprocessing (which includes palm extraction from hand images), Gabor feature extraction, comparison by Hamming distance, and score fusion. Fusion possibilities are discussed and tested first using a bimodal database of 130 subjects that we designed (uB database), and then two common public biometric databases (AR for face and PolyU for palmprint). High performance has been obtained for recognition and verification purpose: a recognition rate of 97.49% with AR-PolyU database and an equal error rate of 1.10% on the uB database using only two training samples per subject have been obtained. Hardware results demonstrate that preprocessing can easily be performed during the acquisition phase, and multimodal biometric recognition can be treated almost instantly (0.4 ms on FPGA). We show the feasibility of a robust and efficient multimodal hardware biometric system that offers several advantages, such as user-friendliness and flexibility.

An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies.

PubMed

Yang, Xiaohuan; Huang, Yaohuan; Dong, Pinliang; Jiang, Dong; Liu, Honghui

2009-01-01

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Biometric Fusion Demonstration System Scientific Report

DTIC Science & Technology

2004-03-01

verification and facial recognition , searching watchlist databases comprised of full or partial facial images or voice recordings. Multiple-biometric...17 2.2.1.1 Fingerprint and Facial Recognition ............................... 17...iv DRDC Ottawa CR 2004 – 056 2.2.1.2 Iris Recognition and Facial Recognition ........................ 18

Fuzzy Clustering Applied to ROI Detection in Helical Thoracic CT Scans with a New Proposal and Variants

PubMed Central

Castro, Alfonso; Boveda, Carmen; Arcay, Bernardino; Sanjurjo, Pedro

2016-01-01

The detection of pulmonary nodules is one of the most studied problems in the field of medical image analysis due to the great difficulty in the early detection of such nodules and their social impact. The traditional approach involves the development of a multistage CAD system capable of informing the radiologist of the presence or absence of nodules. One stage in such systems is the detection of ROI (regions of interest) that may be nodules in order to reduce the space of the problem. This paper evaluates fuzzy clustering algorithms that employ different classification strategies to achieve this goal. After characterising these algorithms, the authors propose a new algorithm and different variations to improve the results obtained initially. Finally it is shown as the most recent developments in fuzzy clustering are able to detect regions that may be nodules in CT studies. The algorithms were evaluated using helical thoracic CT scans obtained from the database of the LIDC (Lung Image Database Consortium). PMID:27517049

Increasing Receipt of High-Tech/High-Cost Imaging and Its Determinants in the Last Month of Taiwanese Patients With Metastatic Cancer, 2001–2010

PubMed Central

Liu, Tsang-Wu; Hung, Yen-Ni; Soong, Thomas C.; Tang, Siew Tzuh

2015-01-01

Abstract One strategy for controlling the skyrocketing costs of cancer care may be to target high-tech/high-cost imaging at the end of life (EOL). This population-based study investigated receipt of high-tech/high-cost imaging and its determinants for Taiwanese patients with metastatic cancer in their last month of life. Individual patient-level data were linked with encrypted identification numbers from computerized administrative data in Taiwan, that is, the National Register of Deaths Database, Cancer Registration System database, and National Health Insurance claims datasets, Database of Medical Care Institutions Status, and national census statistics (population/household income). We identified receipt of computerized tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and radionuclide bone scans (BSs) for 236,911 Taiwanese cancer decedents with metastatic disease, 2001 to 2010. Associations of patient, physician, hospital, and regional factors with receiving CT, MRI, and bone scan in the last month of life were evaluated by multilevel generalized linear-mixed models. Over one-third (average [range]: 36.11% [33.07%–37.31%]) of patients with metastatic cancer received at least 1 high-tech/high-cost imaging modality in their last month (usage rates for CT, MRI, PET, and BS were 31.05%, 5.81%, 0.25%, and 8.15%, respectively). In 2001 to 2010, trends of receipt increased for CT (27.96–32.22%), MRI (4.34–6.70%), and PET (0.00–0.62%), but decreased for BS (9.47–6.57%). Facilitative determinants with consistent trends for at least 2 high-tech/high-cost imaging modalities were male gender, younger age, married, rural residence, lung cancer diagnosis, dying within 1 to 2 years of diagnosis, not under medical oncology care, and receiving care at a teaching hospital with a larger volume of terminally ill cancer patients and greater EOL care intensity. Undergoing high-tech/high-cost imaging at EOL generally was not associated with regional characteristics, healthcare resources, and EOL care intensity. To more effectively use high-tech/high-cost imaging at EOL, clinical and financial interventions should target nonmedical oncologists/hematologists affiliated with teaching hospitals that tend to aggressively treat high volumes of terminally ill cancer patients, thereby avoiding unnecessary EOL care spending and transforming healthcare systems into affordable high-quality cancer care delivery systems. PMID:26266390

A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

PubMed Central

Xie, Jin; Zhang, Lei; You, Jane; Zhang, David; Qu, Xiaofeng

2012-01-01

Human hand back skin texture (HBST) is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands). An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the l1 -minimization based sparse representation (SR) technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification. PMID:23012512

Automatic Reacquisition of Satellite Positions by Detecting Their Expected Streaks in Astronomical Images

NASA Astrophysics Data System (ADS)

Levesque, M.

Artificial satellites, and particularly space junk, drift continuously from their known orbits. In the surveillance-of-space context, they must be observed frequently to ensure that the corresponding orbital parameter database entries are up-to-date. Autonomous ground-based optical systems are periodically tasked to observe these objects, calculate the difference between their predicted and real positions and update object orbital parameters. The real satellite positions are provided by the detection of the satellite streaks in the astronomical images specifically acquired for this purpose. This paper presents the image processing techniques used to detect and extract the satellite positions. The methodology includes several processing steps including: image background estimation and removal, star detection and removal, an iterative matched filter for streak detection, and finally false alarm rejection algorithms. This detection methodology is able to detect very faint objects. Simulated data were used to evaluate the methodology's performance and determine the sensitivity limits where the algorithm can perform detection without false alarm, which is essential to avoid corruption of the orbital parameter database.

Smart travel guide: from internet image database to intelligent system

NASA Astrophysics Data System (ADS)

Chareyron, Ga"l.; Da Rugna, Jérome; Cousin, Saskia

2011-02-01

To help the tourist to discover a city, a region or a park, many options are provided by public tourism travel centers, by free online guides or by dedicated book guides. Nonetheless, these guides provide only mainstream information which are not conform to a particular tourist behavior. On the other hand, we may find several online image databases allowing users to upload their images and to localize each image on a map. These websites are representative of tourism practices and constitute a proxy to analyze tourism flows. Then, this work intends to answer this question: knowing what I have visited and what other people have visited, where should I go now? This process needs to profile users, sites and photos. our paper presents the acquired data and relationship between photographers, sites and photos and introduces the model designed to correctly estimate the site interest of each tourism point. The third part shows an application of our schema: a smart travel guide on geolocated mobile devices. This android application is a travel guide truly matching the user wishes.

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.

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.

Supporting NASA Facilities Through GIS

NASA Technical Reports Server (NTRS)

Ingham, Mary E.

2000-01-01

The NASA GIS Team supports NASA facilities and partners in the analysis of spatial data. Geographic Information System (G[S) is an integration of computer hardware, software, and personnel linking topographic, demographic, utility, facility, image, and other geo-referenced data. The system provides a graphic interface to relational databases and supports decision making processes such as planning, design, maintenance and repair, and emergency response.

Semantic Segmentation and Unregistered Building Detection from Uav Images Using a Deconvolutional Network

NASA Astrophysics Data System (ADS)

Ham, S.; Oh, Y.; Choi, K.; Lee, I.

2018-05-01

Detecting unregistered buildings from aerial images is an important task for urban management such as inspection of illegal buildings in green belt or update of GIS database. Moreover, the data acquisition platform of photogrammetry is evolving from manned aircraft to UAVs (Unmanned Aerial Vehicles). However, it is very costly and time-consuming to detect unregistered buildings from UAV images since the interpretation of aerial images still relies on manual efforts. To overcome this problem, we propose a system which automatically detects unregistered buildings from UAV images based on deep learning methods. Specifically, we train a deconvolutional network with publicly opened geospatial data, semantically segment a given UAV image into a building probability map and compare the building map with existing GIS data. Through this procedure, we could detect unregistered buildings from UAV images automatically and efficiently. We expect that the proposed system can be applied for various urban management tasks such as monitoring illegal buildings or illegal land-use change.

Finger vein verification system based on sparse representation.

PubMed

Xin, Yang; Liu, Zhi; Zhang, Haixia; Zhang, Hong

2012-09-01

Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

Radiotherapy supporting system based on the image database using IS&C magneto-optical disk

NASA Astrophysics Data System (ADS)

Ando, Yutaka; Tsukamoto, Nobuhiro; Kunieda, Etsuo; Kubo, Atsushi

1994-05-01

Since radiation oncologists make the treatment plan by prior experience, information about previous cases is helpful in planning the radiation treatment. We have developed an supporting system for the radiation therapy. The case-based reasoning method was implemented in order to search old treatments and images of past cases. This system evaluates similarities between the current case and all stored cases (case base). The portal images of the similar cases can be retrieved for reference images, as well as treatment records which show examples of the radiation treatment. By this system radiotherapists can easily make suitable plans of the radiation therapy. This system is useful to prevent inaccurate plannings due to preconceptions and/or lack of knowledge. Images were stored into magneto-optical disks and the demographic data is recorded to the hard disk which is equipped in the personal computer. Images can be displayed quickly on the radiotherapist's demands. The radiation oncologist can refer past cases which are recorded in the case base and decide the radiation treatment of the current case. The file and data format of magneto-optical disk is the IS&C format. This format provides the interchangeability and reproducibility of the medical information which includes images and other demographic data.

Curating and Preserving the Big Canopy Database System: an Active Curation Approach using SEAD

NASA Astrophysics Data System (ADS)

Myers, J.; Cushing, J. B.; Lynn, P.; Weiner, N.; Ovchinnikova, A.; Nadkarni, N.; McIntosh, A.

2015-12-01

Modern research is increasingly dependent upon highly heterogeneous data and on the associated cyberinfrastructure developed to organize, analyze, and visualize that data. However, due to the complexity and custom nature of such combined data-software systems, it can be very challenging to curate and preserve them for the long term at reasonable cost and in a way that retains their scientific value. In this presentation, we describe how this challenge was met in preserving the Big Canopy Database (CanopyDB) system using an agile approach and leveraging the Sustainable Environment - Actionable Data (SEAD) DataNet project's hosted data services. The CanopyDB system was developed over more than a decade at Evergreen State College to address the needs of forest canopy researchers. It is an early yet sophisticated exemplar of the type of system that has become common in biological research and science in general, including multiple relational databases for different experiments, a custom database generation tool used to create them, an image repository, and desktop and web tools to access, analyze, and visualize this data. SEAD provides secure project spaces with a semantic content abstraction (typed content with arbitrary RDF metadata statements and relationships to other content), combined with a standards-based curation and publication pipeline resulting in packaged research objects with Digital Object Identifiers. Using SEAD, our cross-project team was able to incrementally ingest CanopyDB components (images, datasets, software source code, documentation, executables, and virtualized services) and to iteratively define and extend the metadata and relationships needed to document them. We believe that both the process, and the richness of the resultant standards-based (OAI-ORE) preservation object, hold lessons for the development of best-practice solutions for preserving scientific data in association with the tools and services needed to derive value from it.

Atmospheric turbulence and sensor system effects on biometric algorithm performance

NASA Astrophysics Data System (ADS)

Espinola, Richard L.; Leonard, Kevin R.; Byrd, Kenneth A.; Potvin, Guy

2015-05-01

Biometric technologies composed of electro-optical/infrared (EO/IR) sensor systems and advanced matching algorithms are being used in various force protection/security and tactical surveillance applications. To date, most of these sensor systems have been widely used in controlled conditions with varying success (e.g., short range, uniform illumination, cooperative subjects). However the limiting conditions of such systems have yet to be fully studied for long range applications and degraded imaging environments. Biometric technologies used for long range applications will invariably suffer from the effects of atmospheric turbulence degradation. Atmospheric turbulence causes blur, distortion and intensity fluctuations that can severely degrade image quality of electro-optic and thermal imaging systems and, for the case of biometrics technology, translate to poor matching algorithm performance. In this paper, we evaluate the effects of atmospheric turbulence and sensor resolution on biometric matching algorithm performance. We use a subset of the Facial Recognition Technology (FERET) database and a commercial algorithm to analyze facial recognition performance on turbulence degraded facial images. The goal of this work is to understand the feasibility of long-range facial recognition in degraded imaging conditions, and the utility of camera parameter trade studies to enable the design of the next generation biometrics sensor systems.

[Expert systems and automatic diagnostic systems in histopathology--a review].

PubMed

Tamai, S

1999-02-01

In this decade, the pathological information system has gradually been settled in many hospitals in Japan. Pathological reports and images are now digitized and managed in the database, and are referred by clinicians at the peripherals. Tele-pathology is also developing; and its users are increasing. However, in many occasions, the problem solving in diagnostic pathology is completely dependent on the solo-pathologist. Considering the need for timely and efficient supports to the solo-pathologist, I reviewed the papers on the knowledge-based interactive expert systems. The interpretations of the histopathological images are dependent on the pathologist, and these expert systems have been evaluated as "educational". With the view of the success in the cytological screening, the development of "image-analysis-based" automatic "histopathological image" classifier has been on ongoing challenges. Our 3 years experience of the development of the pathological image classifier using the artificial neural networks technology is briefly presented. This classifier provides us a "fitting rate" for the individual diagnostic pattern of the breast tumors, such as "fibroadenoma pattern". The diagnosis assisting system with computer technology should provide pathologists, especially solo-pathologists, a useful tool for the quality assurance and improvement of pathological diagnosis.

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).