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Sample records for photo image retrieval

  1. Imaging Technology in Libraries: Photo CD Offers New Possibilities.

    ERIC Educational Resources Information Center

    Beiser, Karl

    1993-01-01

    Describes Kodak's Photo CD technology, a format for the storage and retrieval of photographic images in electronic form. Highlights include current and future Photo CD formats; computer imaging technology; ownership issues; hardware for using Photo CD; software; library and information center applications, including image collections and…

  2. Magneto-photo-acoustic imaging

    PubMed Central

    Qu, Min; Mallidi, Srivalleesha; Mehrmohammadi, Mohammad; Truby, Ryan; Homan, Kimberly; Joshi, Pratixa; Chen, Yun-Sheng; Sokolov, Konstantin; Emelianov, Stanislav

    2011-01-01

    Magneto-photo-acoustic imaging, a technique based on the synergy of magneto-motive ultrasound, photoacoustic and ultrasound imaging, is introduced. Hybrid nanoconstructs, liposomes encapsulating gold nanorods and iron oxide nanoparticles, were used as a dual-contrast agent for magneto-photo-acoustic imaging. Tissue-mimicking phantom and macrophage cells embedded in ex vivo porcine tissue were used to demonstrate that magneto-photo-acoustic imaging is capable of visualizing the location of cells or tissues labeled with dual-contrast nanoparticles with sufficient contrast, excellent contrast resolution and high spatial resolution in the context of the anatomical structure of the surrounding tissues. Therefore, magneto-photo-acoustic imaging is capable of identifying the nanoparticle-labeled pathological regions from the normal tissue, providing a promising platform to noninvasively diagnose and characterize pathologies. PMID:21339883

  3. Mobile medical image retrieval

    NASA Astrophysics Data System (ADS)

    Duc, Samuel; Depeursinge, Adrien; Eggel, Ivan; Müller, Henning

    2011-03-01

    Images are an integral part of medical practice for diagnosis, treatment planning and teaching. Image retrieval has gained in importance mainly as a research domain over the past 20 years. Both textual and visual retrieval of images are essential. In the process of mobile devices becoming reliable and having a functionality equaling that of formerly desktop clients, mobile computing has gained ground and many applications have been explored. This creates a new field of mobile information search & access and in this context images can play an important role as they often allow understanding complex scenarios much quicker and easier than free text. Mobile information retrieval in general has skyrocketed over the past year with many new applications and tools being developed and all sorts of interfaces being adapted to mobile clients. This article describes constraints of an information retrieval system including visual and textual information retrieval from the medical literature of BioMedCentral and of the RSNA journals Radiology and Radiographics. Solutions for mobile data access with an example on an iPhone in a web-based environment are presented as iPhones are frequently used and the operating system is bound to become the most frequent smartphone operating system in 2011. A web-based scenario was chosen to allow for a use by other smart phone platforms such as Android as well. Constraints of small screens and navigation with touch screens are taken into account in the development of the application. A hybrid choice had to be taken to allow for taking pictures with the cell phone camera and upload them for visual similarity search as most producers of smart phones block this functionality to web applications. Mobile information access and in particular access to images can be surprisingly efficient and effective on smaller screens. Images can be read on screen much faster and relevance of documents can be identified quickly through the use of images contained in

  4. Web Mining for Web Image Retrieval.

    ERIC Educational Resources Information Center

    Chen, Zheng; Wenyin, Liu; Zhang, Feng; Li, Mingjing; Zhang, Hongjiang

    2001-01-01

    Presents a prototype system for image retrieval from the Internet using Web mining. Discusses the architecture of the Web image retrieval prototype; document space modeling; user log mining; and image retrieval experiments to evaluate the proposed system. (AEF)

  5. 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.

  6. Digital Image Access & Retrieval.

    ERIC Educational Resources Information Center

    Heidorn, P. Bryan, Ed.; Sandore, Beth, Ed.

    Recent technological advances in computing and digital imaging technology have had immediate and permanent consequences for visual resource collections. Libraries are involved in organizing and managing large visual resource collections. The central challenges in working with digital image collections mirror those that libraries have sought to…

  7. 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

  8. Validating a Geographical Image Retrieval System.

    ERIC Educational Resources Information Center

    Zhu, Bin; Chen, Hsinchun

    2000-01-01

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

  9. Geometrical Calibration of the Photo-Spectral System and Digital Maps Retrieval

    NASA Astrophysics Data System (ADS)

    Bruchkouskaya, S.; Skachkova, A.; Katkovski, L.; Martinov, A.

    2013-12-01

    Imaging systems for remote sensing of the Earth are required to demonstrate high metric accuracy of the picture which can be provided through preliminary geometrical calibration of optical systems. Being defined as a result of the geometrical calibration, parameters of internal and external orientation of the cameras are needed while solving such problems of image processing, as orthotransformation, geometrical correction, geographical coordinate fixing, scale adjustment and image registration from various channels and cameras, creation of image mosaics of filmed territories, and determination of geometrical characteristics of objects in the images. The geometrical calibration also helps to eliminate image deformations arising due to manufacturing defects and errors in installation of camera elements and photo receiving matrices as well as those resulted from lens distortions. A Photo-Spectral System (PhSS), which is intended for registering reflected radiation spectra of underlying surfaces in a wavelength range from 350 nm to 1050 nm and recording images of high spatial resolution, has been developed at the A.N. Sevchenko Research Institute of Applied Physical Problems of the Belarusian State University. The PhSS has undergone flight tests over the territory of Belarus onboard the Antonov AN-2 aircraft with the aim to obtain visible range images of the underlying surface. Then we performed the geometrical calibration of the PhSS and carried out the correction of images obtained during the flight tests. Furthermore, we have plotted digital maps of the terrain using the stereo pairs of images acquired from the PhSS and evaluated the accuracy of the created maps. Having obtained the calibration parameters, we apply them for correction of the images from another identical PhSS device, which is located at the Russian Orbital Segment of the International Space Station (ROS ISS), aiming to retrieve digital maps of the terrain with higher accuracy.

  10. Why Do Photo Finish Images Look Weird?

    ERIC Educational Resources Information Center

    Gregorcic, Bor; Planinsic, Gorazd

    2012-01-01

    This paper deals with effects that appear on photographs of rotating objects when taken by a photo finish camera, a rolling shutter camera or a computer scanner. These effects are very similar to Roget's palisade illusion. A simple quantitative analysis of the images is also provided. The effects are explored using a computer scanner in a way that…

  11. Document image retrieval through word shape coding.

    PubMed

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

    2008-11-01

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

  12. Real-time photo-magnetic imaging.

    PubMed

    Nouizi, Farouk; Erkol, Hakan; Luk, Alex; Unlu, Mehmet B; Gulsen, Gultekin

    2016-10-01

    We previously introduced a new high resolution diffuse optical imaging modality termed, photo-magnetic imaging (PMI). PMI irradiates the object under investigation with near-infrared light and monitors the variations of temperature using magnetic resonance thermometry (MRT). In this paper, we present a real-time PMI image reconstruction algorithm that uses analytic methods to solve the forward problem and assemble the Jacobian matrix much faster. The new algorithm is validated using real MRT measured temperature maps. In fact, it accelerates the reconstruction process by more than 250 times compared to a single iteration of the FEM-based algorithm, which opens the possibility for the real-time PMI.

  13. Scalable ranked retrieval using document images

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  14. Simultenious binary hash and features learning for image retrieval

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  15. Feature hashing for fast image retrieval

    NASA Astrophysics Data System (ADS)

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

    2018-03-01

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

  16. Phase retrieval by coherent modulation imaging.

    PubMed

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

    2016-11-18

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

  17. Content-Based Medical Image Retrieval

    NASA Astrophysics Data System (ADS)

    Müller, Henning; Deserno, Thomas M.

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

  18. Medical Image Retrieval: A Multimodal Approach

    PubMed Central

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

    2014-01-01

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

  19. Storage and retrieval of digital images in dermatology.

    PubMed

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

    1995-11-01

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

  20. Toward privacy-preserving JPEG image retrieval

    NASA Astrophysics Data System (ADS)

    Cheng, Hang; Wang, Jingyue; Wang, Meiqing; Zhong, Shangping

    2017-07-01

    This paper proposes a privacy-preserving retrieval scheme for JPEG images based on local variance. Three parties are involved in the scheme: the content owner, the server, and the authorized user. The content owner encrypts JPEG images for privacy protection by jointly using permutation cipher and stream cipher, and then, the encrypted versions are uploaded to the server. With an encrypted query image provided by an authorized user, the server may extract blockwise local variances in different directions without knowing the plaintext content. After that, it can calculate the similarity between the encrypted query image and each encrypted database image by a local variance-based feature comparison mechanism. The authorized user with the encryption key can decrypt the returned encrypted images with plaintext content similar to the query image. The experimental results show that the proposed scheme not only provides effective privacy-preserving retrieval service but also ensures both format compliance and file size preservation for encrypted JPEG images.

  1. 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.

  2. Automatic visibility retrieval from thermal camera images

    NASA Astrophysics Data System (ADS)

    Dizerens, Céline; Ott, Beat; Wellig, Peter; Wunderle, Stefan

    2017-10-01

    This study presents an automatic visibility retrieval of a FLIR A320 Stationary Thermal Imager installed on a measurement tower on the mountain Lagern located in the Swiss Jura Mountains. Our visibility retrieval makes use of edges that are automatically detected from thermal camera images. Predefined target regions, such as mountain silhouettes or buildings with high thermal differences to the surroundings, are used to derive the maximum visibility distance that is detectable in the image. To allow a stable, automatic processing, our procedure additionally removes noise in the image and includes automatic image alignment to correct small shifts of the camera. We present a detailed analysis of visibility derived from more than 24000 thermal images of the years 2015 and 2016 by comparing them to (1) visibility derived from a panoramic camera image (VISrange), (2) measurements of a forward-scatter visibility meter (Vaisala FD12 working in the NIR spectra), and (3) modeled visibility values using the Thermal Range Model TRM4. Atmospheric conditions, mainly water vapor from European Center for Medium Weather Forecast (ECMWF), were considered to calculate the extinction coefficients using MODTRAN. The automatic visibility retrieval based on FLIR A320 images is often in good agreement with the retrieval from the systems working in different spectral ranges. However, some significant differences were detected as well, depending on weather conditions, thermal differences of the monitored landscape, and defined target size.

  3. Segmenting human from photo images based on a coarse-to-fine scheme.

    PubMed

    Lu, Huchuan; Fang, Guoliang; Shao, Xinqing; Li, Xuelong

    2012-06-01

    Human segmentation in photo images is a challenging and important problem that finds numerous applications ranging from album making and photo classification to image retrieval. Previous works on human segmentation usually demand a time-consuming training phase for complex shape-matching processes. In this paper, we propose a straightforward framework to automatically recover human bodies from color photos. Employing a coarse-to-fine strategy, we first detect a coarse torso (CT) using the multicue CT detection algorithm and then extract the accurate region of the upper body. Then, an iterative multiple oblique histogram algorithm is presented to accurately recover the lower body based on human kinematics. The performance of our algorithm is evaluated on our own data set (contains 197 images with human body region ground truth data), VOC 2006, and the 2010 data set. Experimental results demonstrate the merits of the proposed method in segmenting a person with various poses.

  4. Secure image retrieval with multiple keys

    NASA Astrophysics Data System (ADS)

    Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

    2018-03-01

    This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

  5. 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).

  6. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-006). March 2005. JACKBOLTS BETWEEN MAGNET AND MAGNET FOUNDATION, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  7. 7. THIS PHOTO IMAGE WAS TAKEN, LOOKING NORTH FROM THE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    7. THIS PHOTO IMAGE WAS TAKEN, LOOKING NORTH FROM THE SOUTH BANK TOWARD THE WEST (DOWNSTREAM) SIDE OF THE BRIDGE. - Cement Plant Road Bridge, Spanning Leatherwood Creek on County Road 50 South, Bedford, Lawrence County, IN

  8. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-158). March 2005. CONNECTION OF MAGNET ROOM CRANE TO OUTER TRACK, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  9. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-047). March 2005. AREA OF MAGNET REMOVAL, NORTHEAST QUADRANT, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  10. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-015). March 2005. INTERIOR WALL OF MAGNET INSIDE CENTER OF BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  11. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-054). March 2005. LOCAL INJECTOR ENTERING SHIELDING, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  12. 19. The first floor. A photo image of the public ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    19. The first floor. A photo image of the public entry, elevator foyer and the rear of the central display windows. - John T. Beasley Building, 632 Cherry Street (between Sixth & Seventh Streets), Terre Haute, Vigo County, IN

  13. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-027). March 2005. MOUSE AT EAST TANGENT, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  14. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-004). March 2005. ENTRY TO IGLOO, ILLUSTRATING THICKNESS OF IGLOO WALL, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  15. 11. Photo image looking northwest of the relocation office and ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    11. Photo image looking northwest of the relocation office and other administrative buildings. - Fort Benjamin Harrison, East Fifty-sixth Street (Aultman Avenue) & Glenn Road, Lawrence, Marion County, IN

  16. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-066). March 2005. LOCAL INJECTOR, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  17. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-043). March 2005. MOUSE AT EAST TANGENT, PLUNGING MECHANISM, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  18. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-077). March 2005. STUB OF SUPERHILAC BEAM, ENTERING SHIELDING, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  19. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-026). March 2005. MOUSE AT EAST TANGENT, LOOKING TOWARD EAST TANGENT, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  20. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-005). March 2005. PASSAGEWAY UNDER SOUTHEAST QUADRANT, AIR DUCT OPENINGS, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  1. 5. A PHOTO IMAGE FROM THE WEST SIDEWALK LOOKING EAST ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    5. A PHOTO IMAGE FROM THE WEST SIDEWALK LOOKING EAST TOWARD THE ENTRY GATES AND PORTIONS OF RILEY PARK - Delphi Bridge on U.S. Route 421, Spanning Deer Creek at U.S. Route 421, Delphi, Carroll County, IN

  2. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection XBD200503-00117-089). March 2005. GENERATOR PIT AREA, CONCRETE FOUNDATION FOR EQUIPMENT MOUNTS, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  3. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-082). June 2005. CEILING AND CRANE OF BUILDING 51A, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  4. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-107). March 2005. NORTH FAN, FAN ROOM, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  5. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-106). March 2005. SOUTH FAN, FAN ROOM, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  6. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-110). March 2005. SOUTH FAN FROM MEZZANINE, FAN ROOM, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  7. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-143). March 2005. BUILDING 51A, EXTERIOR WALL, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  8. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-052). March 2005. LOCAL INJECTOR, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  9. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-087). March 2005. GENERATOR PIT AREA, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  10. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-012). March 2005. PASSAGEWAY UNDER QUADRANT AND DIFFUSION PUMPS, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  11. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-050). March 2005. DIFFUSION PUMPS UNDER WEST TANGENT, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  12. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-108). March 2005. FAN ROOM WITH STAIR TO FILTER BANKS, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  13. Active learning methods for interactive image retrieval.

    PubMed

    Gosselin, Philippe Henri; Cord, Matthieu

    2008-07-01

    Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

  14. Phase retrieval by coherent modulation imaging

    SciTech Connect

    Zhang, Fucai; Chen, Bo; Morrison, Graeme R.

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

  15. Phase retrieval by coherent modulation imaging

    DOE PAGES

    Zhang, Fucai; Chen, Bo; Morrison, Graeme R.; ...

    2016-11-18

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

  16. Covert photo classification by fusing image features and visual attributes.

    PubMed

    Lang, Haitao; Ling, Haibin

    2015-10-01

    In this paper, we study a novel problem of classifying covert photos, whose acquisition processes are intentionally concealed from the subjects being photographed. Covert photos are often privacy invasive and, if distributed over Internet, can cause serious consequences. Automatic identification of such photos, therefore, serves as an important initial step toward further privacy protection operations. The problem is, however, very challenging due to the large semantic similarity between covert and noncovert photos, the enormous diversity in the photographing process and environment of cover photos, and the difficulty to collect an effective data set for the study. Attacking these challenges, we make three consecutive contributions. First, we collect a large data set containing 2500 covert photos, each of them is verified rigorously and carefully. Second, we conduct a user study on how humans distinguish covert photos from noncovert ones. The user study not only provides an important evaluation baseline, but also suggests fusing heterogeneous information for an automatic solution. Our third contribution is a covert photo classification algorithm that fuses various image features and visual attributes in the multiple kernel learning framework. We evaluate the proposed approach on the collected data set in comparison with other modern image classifiers. The results show that our approach achieves an average classification rate (1-EER) of 0.8940, which significantly outperforms other competitors as well as human's performance.

  17. Retrieval and classification of food images.

    PubMed

    Farinella, Giovanni Maria; Allegra, Dario; Moltisanti, Marco; Stanco, Filippo; Battiato, Sebastiano

    2016-10-01

    Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As first contribution we present a survey of the studies in the context of food image processing from the early attempts to the current state-of-the-art methods. Since retrieval and classification engines able to work on food images are required to build automatic systems for diet monitoring (e.g., to be embedded in wearable cameras), we focus our attention on the aspect of the representation of the food images because it plays a fundamental role in the understanding engines. The food retrieval and classification is a challenging task since the food presents high variableness and an intrinsic deformability. To properly study the peculiarities of different image representations we propose the UNICT-FD1200 dataset. It was composed of 4754 food images of 1200 distinct dishes acquired during real meals. Each food plate is acquired multiple times and the overall dataset presents both geometric and photometric variabilities. The images of the dataset have been manually labeled considering 8 categories: Appetizer, Main Course, Second Course, Single Course, Side Dish, Dessert, Breakfast, Fruit. We have performed tests employing different representations of the state-of-the-art to assess the related performances on the UNICT-FD1200 dataset. Finally, we propose a new representation based on the perceptual concept of Anti-Textons which is able to encode spatial information between Textons outperforming other representations in the context of food retrieval and Classification. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Photo-induced ultrasound microscopy for photo-acoustic imaging of non-absorbing specimens

    NASA Astrophysics Data System (ADS)

    Tcarenkova, Elena; Koho, Sami V.; Hänninen, Pekka E.

    2017-08-01

    Photo-Acoustic Microscopy (PAM) has raised high interest in in-vivo imaging due to its ability to preserve the near-diffraction limited spatial resolution of optical microscopes, whilst extending the penetration depth to the mm-range. Another advantage of PAM is that it is a label-free technique - any substance that absorbs PAM excitation laser light can be viewed. However, not all sample structures desired to be observed absorb sufficiently to provide contrast for imaging. This work describes a novel imaging method that makes it possible to visualize optically transparent samples that lack intrinsic photo-acoustic contrast, without the addition of contrast agents. A thin, strongly light absorbing layer next to sample is used to generate a strong ultrasonic signal. This signal, when recorded from opposite side, contains ultrasonic transmission information of the sample and thus the method can be used to obtain an ultrasound transmission image on any PAM.

  19. Storage and retrieval of large digital images

    DOEpatents

    Bradley, J.N.

    1998-01-20

    Image compression and viewing are implemented with (1) a method for performing DWT-based compression on a large digital image with a computer system possessing a two-level system of memory and (2) a method for selectively viewing areas of the image from its compressed representation at multiple resolutions and, if desired, in a client-server environment. The compression of a large digital image I(x,y) is accomplished by first defining a plurality of discrete tile image data subsets T{sub ij}(x,y) that, upon superposition, form the complete set of image data I(x,y). A seamless wavelet-based compression process is effected on I(x,y) that is comprised of successively inputting the tiles T{sub ij}(x,y) in a selected sequence to a DWT routine, and storing the resulting DWT coefficients in a first primary memory. These coefficients are periodically compressed and transferred to a secondary memory to maintain sufficient memory in the primary memory for data processing. The sequence of DWT operations on the tiles T{sub ij}(x,y) effectively calculates a seamless DWT of I(x,y). Data retrieval consists of specifying a resolution and a region of I(x,y) for display. The subset of stored DWT coefficients corresponding to each requested scene is determined and then decompressed for input to an inverse DWT, the output of which forms the image display. The repeated process whereby image views are specified may take the form an interaction with a computer pointing device on an image display from a previous retrieval. 6 figs.

  20. Storage and retrieval of large digital images

    DOEpatents

    Bradley, Jonathan N.

    1998-01-01

    Image compression and viewing are implemented with (1) a method for performing DWT-based compression on a large digital image with a computer system possessing a two-level system of memory and (2) a method for selectively viewing areas of the image from its compressed representation at multiple resolutions and, if desired, in a client-server environment. The compression of a large digital image I(x,y) is accomplished by first defining a plurality of discrete tile image data subsets T.sub.ij (x,y) that, upon superposition, form the complete set of image data I(x,y). A seamless wavelet-based compression process is effected on I(x,y) that is comprised of successively inputting the tiles T.sub.ij (x,y) in a selected sequence to a DWT routine, and storing the resulting DWT coefficients in a first primary memory. These coefficients are periodically compressed and transferred to a secondary memory to maintain sufficient memory in the primary memory for data processing. The sequence of DWT operations on the tiles T.sub.ij (x,y) effectively calculates a seamless DWT of I(x,y). Data retrieval consists of specifying a resolution and a region of I(x,y) for display. The subset of stored DWT coefficients corresponding to each requested scene is determined and then decompressed for input to an inverse DWT, the output of which forms the image display. The repeated process whereby image views are specified may take the form an interaction with a computer pointing device on an image display from a previous retrieval.

  1. SUBMIT YOUR IMAGES TO NASA's "LET IT SNOW" PHOTO CONTEST!

    NASA Image and Video Library

    2017-12-08

    NASA's Global Precipitation Measurement (GPM) mission wants to see your best photos of winter weather! You can submit your images to the contest here: www.flickr.com/groups/gpm-extreme-weather/ To read more about this image and or to see the high res file go to: earthobservatory.nasa.gov/IOTD/view.php?id=80082

  2. Case-based fracture image retrieval.

    PubMed

    Zhou, Xin; Stern, Richard; Müller, Henning

    2012-05-01

    Case-based fracture image retrieval can assist surgeons in decisions regarding new cases by supplying visually similar past cases. This tool may guide fracture fixation and management through comparison of long-term outcomes in similar cases. A fracture image database collected over 10 years at the orthopedic service of the University Hospitals of Geneva was used. This database contains 2,690 fracture cases associated with 43 classes (based on the AO/OTA classification). A case-based retrieval engine was developed and evaluated using retrieval precision as a performance metric. Only cases in the same class as the query case are considered as relevant. The scale-invariant feature transform (SIFT) is used for image analysis. Performance evaluation was computed in terms of mean average precision (MAP) and early precision (P10, P30). Retrieval results produced with the GNU image finding tool (GIFT) were used as a baseline. Two sampling strategies were evaluated. One used a dense 40 × 40 pixel grid sampling, and the second one used the standard SIFT features. Based on dense pixel grid sampling, three unsupervised feature selection strategies were introduced to further improve retrieval performance. With dense pixel grid sampling, the image is divided into 1,600 (40 × 40) square blocks. The goal is to emphasize the salient regions (blocks) and ignore irrelevant regions. Regions are considered as important when a high variance of the visual features is found. The first strategy is to calculate the variance of all descriptors on the global database. The second strategy is to calculate the variance of all descriptors for each case. A third strategy is to perform a thumbnail image clustering in a first step and then to calculate the variance for each cluster. Finally, a fusion between a SIFT-based system and GIFT is performed. A first comparison on the selection of sampling strategies using SIFT features shows that dense sampling using a pixel grid (MAP = 0

  3. A novel image retrieval algorithm based on PHOG and LSH

    NASA Astrophysics Data System (ADS)

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

    2017-08-01

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

  4. Electron-Focus Adjustment for Photo-Optical Imagers

    NASA Technical Reports Server (NTRS)

    Fowler, Walter B.; Flemming, Keith; Ziegler, Michael M.

    1987-01-01

    Internal electron focus made independent of optical focus. Procedure enables fine tuning of internal electron-focusing system of photo-optical imager, without complication by imperfections of associated external optics. Applicable to imager in which electrons emitted from photocathode in optical focal plane, then electrostatically and/or magnetically focused to replica of image in second focal plane containing photodiodes, phototransistorss, charge-coupled devices, multiple-anode outputs, or other detectors.

  5. Vulnerability Analysis of HD Photo Image Viewer Applications

    DTIC Science & Technology

    2007-09-01

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

  6. Multiple Object Retrieval in Image Databases Using Hierarchical Segmentation Tree

    ERIC Educational Resources Information Center

    Chen, Wei-Bang

    2012-01-01

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

  7. Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images

    PubMed Central

    Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro; Aoki, Hiroshi; Takeuchi, Ken; Suzuki, Yasuo

    2017-01-01

    Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy. PMID:28255295

  8. Image Retrieval Method for Multiscale Objects from Optical Colonoscopy Images.

    PubMed

    Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro; Aoki, Hiroshi; Takeuchi, Ken; Suzuki, Yasuo

    2017-01-01

    Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy.

  9. Gaps in content-based image retrieval

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

    Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potentially strong impact in diagnostics, research, and education. Research successes that are increasingly reported in the scientific literature, however, have not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed without sufficient analytical reasoning to the inability of these applications in overcoming the "semantic gap". The semantic gap divides the high-level scene analysis of humans from the low-level pixel analysis of computers. In this paper, we suggest a more systematic and comprehensive view on the concept of gaps in medical CBIR research. In particular, we define a total of 13 gaps that address the image content and features, as well as the system performance and usability. In addition to these gaps, we identify 6 system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application. To illustrate the a posteriori use of our conceptual system, we apply it, initially, to the classification of three medical CBIR implementations: the content-based PACS approach (cbPACS), the medical GNU image finding tool (medGIFT), and the image retrieval in medical applications (IRMA) project. We show that systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

  10. 20. A PHOTO IMAGE OF THE NORTH BANK OF THE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    20. A PHOTO IMAGE OF THE NORTH BANK OF THE ST. JOSEPH'S RIVER IN THE VICINITY OF THE BRIDGE. - County Line Bridge, Spanning St. Joseph River at State Route 219, 0.6 mile south of U.S. Route 20, Osceola, St. Joseph County, IN

  11. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200506-00198-11). June 2005. DUCTWORK BETWEEN FAN ROOM AND PASSAGEWAY UNDER BEVATRON, NORTH SIDE OF ROOM 10, MAIN FLOOR, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  12. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-046). March 2005. ROOF SHIELDING BLOCK AND I-BEAM SUPPORT CONSTRUCTION, CENTER OF BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  13. 7. THIS PHOTO IMAGE LOOKING SOUTHWEST FROM THE LAND BETWEEN ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    7. THIS PHOTO IMAGE LOOKING SOUTHWEST FROM THE LAND BETWEEN THE TWO CREEKS, SHOWS NORTH SIDE OF THE WEST SPAN OF THE BRIDGE, WITH THE TRUNCATED BALUSTRADE AND STEEL I-SECTIONS HOLDING THE SPANDREL WALLS TOGETHER. - Putnam County Bridge No. 111, Spanning Little Walnut Creek on County Road 50, Greencastle, Putnam County, IN

  14. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-129). March 2005. ENTRY TO ROOM 24, MAIN FLOOR, OFFICE-AND-SHOPS SECTION, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  15. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-034). March 2005. MOUSE AT EAST TANGENT WITH COVER CLOSED, LOOKING TOWARD CENTER IGLOO, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  16. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-009). March 2005. OPENINGS OF AIR DUCTS INTO PASSAGEWAY UNDER SOUTHEAST QUADRANT, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  17. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-031). March 2005. MOUSE AT EAST TANGENT, WITH COVER OPEN, LOOKING TOWARD CENTER IGLOO, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  18. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200506-00198-08). June 2005. DUCTWORK BETWEEN FAN ROOM AND PASSAGEWAY UNDER BEVATRON, SOUTH SIDE OF ROOM 10, MAIN FLOOR, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  19. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200506-00218-12). June 2005. DEEP TUNNEL INTO FOUNDATION UNDER BEVATRON, VIEW OF CART ON RAILS FOR TRANSPORTING EQUIPMENT - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  20. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-049). March 2005. TUNNEL ENTRY FROM MAIN FLOOR OF MAGNET ROOM INTO CENTER OF BEVATRON, BENEATH SOUTHWEST QUADRANT - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  1. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-139). March 2005. TOP OF BEVATRON, INCLUDING WOOD STAIRWAY FROM OUTER EDGE OF SHIELDING TO TOP OF ROOF BLOCK SHIELDING - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  2. Photocopy of photograph (digital image located in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image located in LBNL Photo Lab Collection, XBD200503-00117-035). March 2005. WEST TANGENT VIEWED FROM INTERIOR OF BEVATRON. EQUIPMENT ACCESS STAIRWAY ON LEFT - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  3. Photocopy of photograph (digital image maintained in LBNL Photo Lab ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Photocopy of photograph (digital image maintained in LBNL Photo Lab Collection, XBD200503-00117-176). March 2005. CENTRAL COLUMN SUPPORT TO ROOF SHOWING CRANES CENTER SUPPORT TRACK, BEVATRON - University of California Radiation Laboratory, Bevatron, 1 Cyclotron Road, Berkeley, Alameda County, CA

  4. Skin image retrieval using Gabor wavelet texture feature.

    PubMed

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

    2016-12-01

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

  5. Image based book cover recognition and retrieval

    NASA Astrophysics Data System (ADS)

    Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

    2017-11-01

    In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

  6. Advances in photo-thermal infrared imaging microspectroscopy

    NASA Astrophysics Data System (ADS)

    Furstenberg, Robert; Kendziora, Chris; Papantonakis, Michael; Nguyen, Viet; McGill, Andrew

    2013-05-01

    There is a growing need for chemical imaging techniques in many fields of science and technology: forensics, materials science, pharmaceutical and chemical industries, just to name a few. While FTIR micro-spectroscopy is commonly used, its practical resolution limit of about 20 microns or more is often insufficient. Raman micro-spectroscopy provides better spatial resolution (~1 micron), but is not always practical because of samples exhibiting fluorescence or low Raman scattering efficiency. We are developing a non-contact and non-destructive technique we call photo-thermal infrared imaging spectroscopy (PT-IRIS). It involves photo-thermal heating of the sample with a tunable quantum cascade laser and measuring the resulting increase in thermal emission with an infrared detector. Photo-thermal emission spectra resemble FTIR absorbance spectra and can be acquired in both stand-off and microscopy configurations. Furthermore, PT-IRIS allows the acquisition of absorbance-like photo-thermal spectra in a reflected geometry, suitable for field applications and for in-situ study of samples on optically IR-opaque substrates (metals, fabrics, paint, glass etc.). Conventional FTIR microscopes in reflection mode measure the reflectance spectra which are different from absorbance spectra and are usually not catalogued in FTIR spectral libraries. In this paper, we continue developing this new technique. We perform a series of numerical simulations of the laser heating of samples during photo-thermal microscopy. We develop parameterized formulas to help the user pick the appropriate laser illumination power. We also examine the influence of sample geometry on spectral signatures. Finally, we measure and compare photo-thermal and reflectance spectra for two test samples.

  7. Photo acoustic imaging: technology, systems and market trends

    NASA Astrophysics Data System (ADS)

    Faucheux, Marc; d'Humières, Benoît; Cochard, Jacques

    2017-03-01

    Although the Photo Acoustic effect was observed by Graham Bell in 1880, the first applications (gas analysis) occurred in 1970's using the required energetic light pulses from lasers. During mid 1990's medical imaging research begun to use Photo Acoustic effect and in vivo images were obtained in mid-2000. Since 2009, the number of patent related to Photo Acoustic Imaging (PAI) has dramatically increased. PAI machines for pre-clinical and small animal imaging have been being used in a routine way for several years. Based on its very interesting features (non-ionizing radiation, noninvasive, high depth resolution ratio, scalability, moderate price) and because it is able to deliver not only anatomical, but functional and molecular information, PAI is a very promising clinical imaging modality. It penetrates deeper into tissue than OCT (Optical Coherence Tomography) and provides a higher resolution than ultrasounds. The PAI is one of the most growing imaging modality and some innovative clinical systems are planned to be on market in 2017. Our study analyzes the different approaches such as photoacoustic computed tomography, 3D photoacoustic microscopy, multispectral photoacoustic tomography and endoscopy with the recent and tremendous technological progress over the past decade: advances in image reconstruction algorithms, laser technology, ultrasound detectors and miniaturization. We analyze which medical domains and applications are the most concerned and explain what should be the forthcoming medical system in the near future. We segment the market in four parts: Components and R&D, pre-clinical, analytics, clinical. We analyzed what should be, quantitatively and qualitatively, the PAI medical markets in each segment and its main trends. We point out the market accessibility (patents, regulations, clinical evaluations, clinical acceptance, funding). In conclusion, we explain the main market drivers and challenges to overcome and give a road map for medical

  8. Web Image Retrieval Using Self-Organizing Feature Map.

    ERIC Educational Resources Information Center

    Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

    2001-01-01

    Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

  9. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval.

    PubMed

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

    2017-06-01

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

  10. Mobile object retrieval in server-based image databases

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  11. VICAR - VIDEO IMAGE COMMUNICATION AND RETRIEVAL

    NASA Technical Reports Server (NTRS)

    Wall, R. J.

    1994-01-01

    VICAR (Video Image Communication and Retrieval) is a general purpose image processing software system that has been under continuous development since the late 1960's. Originally intended for data from the NASA Jet Propulsion Laboratory's unmanned planetary spacecraft, VICAR is now used for a variety of other applications including biomedical image processing, cartography, earth resources, and geological exploration. The development of this newest version of VICAR emphasized a standardized, easily-understood user interface, a shield between the user and the host operating system, and a comprehensive array of image processing capabilities. Structurally, VICAR can be divided into roughly two parts; a suite of applications programs and an executive which serves as the interfaces between the applications, the operating system, and the user. There are several hundred applications programs ranging in function from interactive image editing, data compression/decompression, and map projection, to blemish, noise, and artifact removal, mosaic generation, and pattern recognition and location. An information management system designed specifically for handling image related data can merge image data with other types of data files. The user accesses these programs through the VICAR executive, which consists of a supervisor and a run-time library. From the viewpoint of the user and the applications programs, the executive is an environment that is independent of the operating system. VICAR does not replace the host computer's operating system; instead, it overlays the host resources. The core of the executive is the VICAR Supervisor, which is based on NASA Goddard Space Flight Center's Transportable Applications Executive (TAE). Various modifications and extensions have been made to optimize TAE for image processing applications, resulting in a user friendly environment. The rest of the executive consists of the VICAR Run-Time Library, which provides a set of subroutines (image

  12. Image analysis supported moss cell disruption in photo-bioreactors.

    PubMed

    Lucumi, A; Posten, C; Pons, M-N

    2005-05-01

    Diverse methods for the disruption of cell entanglements and pellets of the moss Physcomitrella patens were tested in order to improve the homogeneity of suspension cultures. The morphological characterization of the moss was carried out by means of image analysis. Selected morphological parameters were defined and compared to the reduction of the carbon dioxide fixation, and the released pigments after cell disruption. The size control of the moss entanglements based on the rotor stator principle allowed a focused shear stress, avoiding a severe reduction in the photosynthesis. Batch cultures of P. patens in a 30.0-l pilot tubular photo-bioreactor with cell disruption showed no significant variation in growth rate and a delayed cell differentiation, when compared to undisrupted cultures. A highly controlled photoautotrophic culture of P. patens in a scalable photo-bioreactor was established, contributing to the development required for the future use of mosses as producers of relevant heterologous proteins.

  13. Photo-excitable hybrid nanocomposites for image-guided photo/TRAIL synergistic cancer therapy.

    PubMed

    Lin, Gan; Zhang, Yang; Zhu, Congqing; Chu, Chengchao; Shi, Yesi; Pang, Xin; Ren, En; Wu, Yayun; Mi, Peng; Xia, Haiping; Chen, Xiaoyuan; Liu, Gang

    2018-05-22

    Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) can induce apoptosis in cancer cells without toxicity to normal cells. However, the efficiency is greatly limited by its short half-life and wild resistance in various cancer cells. In this study, we reported a micellar hybrid nanoparticle to carry TRAIL ligand (denoted as IPN@TRAIL) for a novel photo-excited TRAIL therapy. These IPN@TRAIL offered increased TRAIL stability, prolonged half-life and enhanced tumor accumulation, monitored by dual mode imaging. Furthermore, IPN@TRAIL nanocomposites enhanced wrapped TRAIL therapeutic efficiency greatly towards resistant cancer cells by TRAIL nanovectorization. More importantly, when upon external laser, these nanocomposites not only triggered tumor photothermal therapy (PTT), but also upregulated the expression of death receptors (DR4 and DR5), resulting in a greater apoptosis mediated by co-delivered TRAIL ligand. Such photo/TRAIL synergistic effect showed its great killing effects in a controllable manner on TRAIL-resistant A549 tumor model bearing mice. Finally, these nanocomposites exhibited rapid clearance without obvious systemic toxicity. All these features rendered our nanocomposites a promising theranostic platform in cancer therapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2012-08-01

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

  15. 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.

  16. Laser-induced photo-thermal strain imaging

    NASA Astrophysics Data System (ADS)

    Choi, Changhoon; Ahn, Joongho; Jeon, Seungwan; Kim, Chulhong

    2018-02-01

    Vulnerable plaque is the one of the leading causes of cardiovascular disease occurrence. However, conventional intravascular imaging techniques suffer from difficulty in finding vulnerable plaque due to limitation such as lack of physiological information, imaging depth, and depth sensitivity. Therefore, new techniques are needed to help determine the vulnerability of plaque, Thermal strain imaging (TSI) is an imaging technique based on ultrasound (US) wave propagation speed that varies with temperature of medium. During temperature increase, strain occurs in the medium and its variation tendency is depending on the type of tissue, which makes it possible to use for tissue differentiation. Here, we demonstrate laser-induced photo-thermal strain imaging (pTSI) to differentiate tissue using an intravascular ultrasound (IVUS) catheter and a 1210-nm continuous-wave laser for heating lipids intensively. During heating, consecutive US images were obtained from a custom-made phantom made of porcine fat and gelatin. A cross correlation-based speckle-tracking algorithm was then applied to calculate the strain of US images. In the strain images, the positive strain produced in lipids (porcine fat) was clearly differentiated from water-bearing tissue (gelatin). This result shows that laser-induced pTSI could be a new method to distinguish lipids in the plaque and can help to differentiate vulnerability of plaque.

  17. Image selection system. [computerized data storage and retrieval system

    NASA Technical Reports Server (NTRS)

    Knutson, M. A.; Hurd, D.; Hubble, L.; Kroeck, R. M.

    1974-01-01

    An image selection (ISS) was developed for the NASA-Ames Research Center Earth Resources Aircraft Project. The ISS is an interactive, graphics oriented, computer retrieval system for aerial imagery. An analysis of user coverage requests and retrieval strategies is presented, followed by a complete system description. Data base structure, retrieval processors, command language, interactive display options, file structures, and the system's capability to manage sets of selected imagery are described. A detailed example of an area coverage request is graphically presented.

  18. Improved image retrieval based on fuzzy colour feature vector

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  19. Modelling Subjectivity in Visual Perception of Orientation for Image Retrieval.

    ERIC Educational Resources Information Center

    Sanchez, D.; Chamorro-Martinez, J.; Vila, M. A.

    2003-01-01

    Discussion of multimedia libraries and the need for storage, indexing, and retrieval techniques focuses on the combination of computer vision and data mining techniques to model high-level concepts for image retrieval based on perceptual features of the human visual system. Uses fuzzy set theory to measure users' assessments and to capture users'…

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  1. Broadband Phase Retrieval for Image-Based Wavefront Sensing

    NASA Technical Reports Server (NTRS)

    Dean, Bruce H.

    2007-01-01

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

  2. Generating region proposals for histopathological whole slide image retrieval.

    PubMed

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

    2018-06-01

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

  3. Precise and Efficient Retrieval of Captioned Images: The MARIE Project.

    ERIC Educational Resources Information Center

    Rowe, Neil C.

    1999-01-01

    The MARIE project explores knowledge-based information retrieval of captioned images of the kind found in picture libraries and on the Internet. MARIE's five-part approach exploits the idea that images are easier to understand with context, especially descriptive text near them, but it also does image analysis. Experiments show MARIE prototypes…

  4. Supervised graph hashing for histopathology image retrieval and classification.

    PubMed

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

    2017-12-01

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

  5. Ex vivo validation of photo-magnetic imaging.

    PubMed

    Luk, Alex; Nouizi, Farouk; Erkol, Hakan; Unlu, Mehmet B; Gulsen, Gultekin

    2017-10-15

    We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions. We have previously demonstrated the feasibility of PMI with experimental studies using tissue simulating agarose phantoms. In this Letter, we present the preliminary ex vivo PMI results obtained with a chicken breast sample. Similarly to the results obtained on phantoms, the reconstructed images reveal that PMI can quantitatively resolve an inclusion with a 3 mm diameter embedded deep in a biological tissue sample with only 10% error. These encouraging results demonstrate the high performance of PMI in ex vivo biological tissue and its potential for in vivo imaging.

  6. Phase retrieval using regularization method in intensity correlation imaging

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  7. Multiview Locally Linear Embedding for Effective Medical Image Retrieval

    PubMed Central

    Shen, Hualei; Tao, Dacheng; Ma, Dianfu

    2013-01-01

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

  8. Textile Retrieval Based on Image Content from CDC and Webcam Cameras in Indoor Environments.

    PubMed

    García-Olalla, Oscar; Alegre, Enrique; Fernández-Robles, Laura; Fidalgo, Eduardo; Saikia, Surajit

    2018-04-25

    Textile based image retrieval for indoor environments can be used to retrieve images that contain the same textile, which may indicate that scenes are related. This makes up a useful approach for law enforcement agencies who want to find evidence based on matching between textiles. In this paper, we propose a novel pipeline that allows searching and retrieving textiles that appear in pictures of real scenes. Our approach is based on first obtaining regions containing textiles by using MSER on high pass filtered images of the RGB, HSV and Hue channels of the original photo. To describe the textile regions, we demonstrated that the combination of HOG and HCLOSIB is the best option for our proposal when using the correlation distance to match the query textile patch with the candidate regions. Furthermore, we introduce a new dataset, TextilTube, which comprises a total of 1913 textile regions labelled within 67 classes. We yielded 84.94% of success in the 40 nearest coincidences and 37.44% of precision taking into account just the first coincidence, which outperforms the current deep learning methods evaluated. Experimental results show that this pipeline can be used to set up an effective textile based image retrieval system in indoor environments.

  9. Textile Retrieval Based on Image Content from CDC and Webcam Cameras in Indoor Environments

    PubMed Central

    García-Olalla, Oscar; Saikia, Surajit

    2018-01-01

    Textile based image retrieval for indoor environments can be used to retrieve images that contain the same textile, which may indicate that scenes are related. This makes up a useful approach for law enforcement agencies who want to find evidence based on matching between textiles. In this paper, we propose a novel pipeline that allows searching and retrieving textiles that appear in pictures of real scenes. Our approach is based on first obtaining regions containing textiles by using MSER on high pass filtered images of the RGB, HSV and Hue channels of the original photo. To describe the textile regions, we demonstrated that the combination of HOG and HCLOSIB is the best option for our proposal when using the correlation distance to match the query textile patch with the candidate regions. Furthermore, we introduce a new dataset, TextilTube, which comprises a total of 1913 textile regions labelled within 67 classes. We yielded 84.94% of success in the 40 nearest coincidences and 37.44% of precision taking into account just the first coincidence, which outperforms the current deep learning methods evaluated. Experimental results show that this pipeline can be used to set up an effective textile based image retrieval system in indoor environments. PMID:29693590

  10. Intelligent retrieval of medical images from the Internet

    NASA Astrophysics Data System (ADS)

    Tang, Yau-Kuo; Chiang, Ted T.

    1996-05-01

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

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

    PubMed

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

    2017-02-01

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

  12. Image Retrieval by Color Semantics with Incomplete Knowledge.

    ERIC Educational Resources Information Center

    Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico

    1998-01-01

    Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)

  13. Hypertext Image Retrieval: The Evolution of an Application.

    ERIC Educational Resources Information Center

    Roberts, G. Louis; Kenney, Carol E.

    1991-01-01

    Describes the development and implementation of a full-text image retrieval system at the Boeing Commercial Airplane Group. The conversion of card formats to a microcomputer-based system using HyperCard is described; the online system architecture is explained; and future plans are discussed, including conversion to digital images. (LRW)

  14. Learning Short Binary Codes for Large-scale Image Retrieval.

    PubMed

    Liu, Li; Yu, Mengyang; Shao, Ling

    2017-03-01

    Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.

  15. Ontology-guided organ detection to retrieve web images of disease manifestation: towards the construction of a consumer-based health image library.

    PubMed

    Chen, Yang; Ren, Xiaofeng; Zhang, Guo-Qiang; Xu, Rong

    2013-01-01

    Visual information is a crucial aspect of medical knowledge. Building a comprehensive medical image base, in the spirit of the Unified Medical Language System (UMLS), would greatly benefit patient education and self-care. However, collection and annotation of such a large-scale image base is challenging. To combine visual object detection techniques with medical ontology to automatically mine web photos and retrieve a large number of disease manifestation images with minimal manual labeling effort. As a proof of concept, we first learnt five organ detectors on three detection scales for eyes, ears, lips, hands, and feet. Given a disease, we used information from the UMLS to select affected body parts, ran the pretrained organ detectors on web images, and combined the detection outputs to retrieve disease images. Compared with a supervised image retrieval approach that requires training images for every disease, our ontology-guided approach exploits shared visual information of body parts across diseases. In retrieving 2220 web images of 32 diseases, we reduced manual labeling effort to 15.6% while improving the average precision by 3.9% from 77.7% to 81.6%. For 40.6% of the diseases, we improved the precision by 10%. The results confirm the concept that the web is a feasible source for automatic disease image retrieval for health image database construction. Our approach requires a small amount of manual effort to collect complex disease images, and to annotate them by standard medical ontology terms.

  16. Measuring and Predicting Tag Importance for Image Retrieval.

    PubMed

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

    2017-12-01

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

  17. Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

    PubMed

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

    2017-07-01

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

  18. A memory learning framework for effective image retrieval.

    PubMed

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

    2005-04-01

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

  19. Retrieval of Sentence Sequences for an Image Stream via Coherence Recurrent Convolutional Networks.

    PubMed

    Park, Cesc Chunseong; Kim, Youngjin; Kim, Gunhee

    2018-04-01

    We propose an approach for retrieving a sequence of natural sentences for an image stream. Since general users often take a series of pictures on their experiences, much online visual information exists in the form of image streams, for which it would better take into consideration of the whole image stream to produce natural language descriptions. While almost all previous studies have dealt with the relation between a single image and a single natural sentence, our work extends both input and output dimension to a sequence of images and a sequence of sentences. For retrieving a coherent flow of multiple sentences for a photo stream, we propose a multimodal neural architecture called coherence recurrent convolutional network (CRCN), which consists of convolutional neural networks, bidirectional long short-term memory (LSTM) networks, and an entity-based local coherence model. Our approach directly learns from vast user-generated resource of blog posts as text-image parallel training data. We collect more than 22 K unique blog posts with 170 K associated images for the travel topics of NYC, Disneyland , Australia, and Hawaii. We demonstrate that our approach outperforms other state-of-the-art image captioning methods for text sequence generation, using both quantitative measures and user studies via Amazon Mechanical Turk.

  20. Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

    PubMed

    Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

    2017-08-25

    We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

  1. Image-based information, communication, and retrieval

    NASA Technical Reports Server (NTRS)

    Bryant, N. A.; Zobrist, A. L.

    1980-01-01

    IBIS/VICAR system combines video image processing and information management. Flexible programs require user to supply only parameters specific to particular application. Special-purpose input/output routines transfer image data with reduced memory requirements. New application programs are easily incorporated. Program is written in FORTRAN IV, Assembler, and OS JCL for batch execution and has been implemented on IBM 360.

  2. Content Based Image Retrieval based on Wavelet Transform coefficients distribution

    PubMed Central

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

    2007-01-01

    In this paper we propose a content based image retrieval method for diagnosis aid in medical fields. We characterize images without extracting significant features by using distribution of coefficients obtained by building signatures from the distribution of wavelet transform. The research is carried out by computing signature distances between the query and database images. Several signatures are proposed; they use a model of wavelet coefficient distribution. To enhance results, a weighted distance between signatures is used and an adapted wavelet base is proposed. Retrieval efficiency is given for different databases including a diabetic retinopathy, a mammography and a face database. Results are promising: the retrieval efficiency is higher than 95% for some cases using an optimization process. PMID:18003013

  3. Dictionary Pruning with Visual Word Significance for Medical Image Retrieval

    PubMed Central

    Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G.; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

    2016-01-01

    Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency. PMID:27688597

  4. Dictionary Pruning with Visual Word Significance for Medical Image Retrieval.

    PubMed

    Zhang, Fan; Song, Yang; Cai, Weidong; Hauptmann, Alexander G; Liu, Sidong; Pujol, Sonia; Kikinis, Ron; Fulham, Michael J; Feng, David Dagan; Chen, Mei

    2016-02-12

    Content-based medical image retrieval (CBMIR) is an active research area for disease diagnosis and treatment but it can be problematic given the small visual variations between anatomical structures. We propose a retrieval method based on a bag-of-visual-words (BoVW) to identify discriminative characteristics between different medical images with Pruned Dictionary based on Latent Semantic Topic description. We refer to this as the PD-LST retrieval. Our method has two main components. First, we calculate a topic-word significance value for each visual word given a certain latent topic to evaluate how the word is connected to this latent topic. The latent topics are learnt, based on the relationship between the images and words, and are employed to bridge the gap between low-level visual features and high-level semantics. These latent topics describe the images and words semantically and can thus facilitate more meaningful comparisons between the words. Second, we compute an overall-word significance value to evaluate the significance of a visual word within the entire dictionary. We designed an iterative ranking method to measure overall-word significance by considering the relationship between all latent topics and words. The words with higher values are considered meaningful with more significant discriminative power in differentiating medical images. We evaluated our method on two public medical imaging datasets and it showed improved retrieval accuracy and efficiency.

  5. Object and image retrieval over the Internet

    NASA Astrophysics Data System (ADS)

    Gilles, Sebastien; Winter, A.; Feldmar, J.; Poirier, N.; Bousquet, R.; Bussy, B.; Lamure, H.; Demarty, C.-H.; Nastar, Chahab

    2000-12-01

    In this article, we describe some of the work that was carried out at LookThatUp for designing an infrastructure enabling image-based search over the Internet. The service was designed to be remotely accessible and easily integrated to partner sites. One application of the technology, called Image-Shopper, is described and demonstrated. The technological basis of the system is then reviewed.

  6. 77 FR 74220 - Certain Digital Photo Frames and Image Display Devices and Components Thereof; Commission...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-12-13

    ... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-807] Certain Digital Photo Frames and Image Display Devices and Components Thereof; Commission Determination Not To Review an Initial... importation, and the sale within the United States after importation of certain digital photo frames and image...

  7. Multi-clues image retrieval based on improved color invariants

    NASA Astrophysics Data System (ADS)

    Liu, Liu; Li, Jian-Xun

    2012-05-01

    At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

  8. Fast content-based image retrieval using dynamic cluster tree

    NASA Astrophysics Data System (ADS)

    Chen, Jinyan; Sun, Jizhou; Wu, Rongteng; Zhang, Yaping

    2008-03-01

    A novel content-based image retrieval data structure is developed in present work. It can improve the searching efficiency significantly. All images are organized into a tree, in which every node is comprised of images with similar features. Images in a children node have more similarity (less variance) within themselves in relative to its parent. It means that every node is a cluster and each of its children nodes is a sub-cluster. Information contained in a node includes not only the number of images, but also the center and the variance of these images. Upon the addition of new images, the tree structure is capable of dynamically changing to ensure the minimization of total variance of the tree. Subsequently, a heuristic method has been designed to retrieve the information from this tree. Given a sample image, the probability of a tree node that contains the similar images is computed using the center of the node and its variance. If the probability is higher than a certain threshold, this node will be recursively checked to locate the similar images. So will its children nodes if their probability is also higher than that threshold. If no sufficient similar images were founded, a reduced threshold value would be adopted to initiate a new seeking from the root node. The search terminates when it found sufficient similar images or the threshold value is too low to give meaningful sense. Experiments have shown that the proposed dynamic cluster tree is able to improve the searching efficiency notably.

  9. Signature detection and matching for document image retrieval.

    PubMed

    Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

    2009-11-01

    As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

  10. Grid-Independent Compressive Imaging and Fourier Phase Retrieval

    ERIC Educational Resources Information Center

    Liao, Wenjing

    2013-01-01

    This dissertation is composed of two parts. In the first part techniques of band exclusion(BE) and local optimization(LO) are proposed to solve linear continuum inverse problems independently of the grid spacing. The second part is devoted to the Fourier phase retrieval problem. Many situations in optics, medical imaging and signal processing call…

  11. Terahertz imaging with compressed sensing and phase retrieval.

    PubMed

    Chan, Wai Lam; Moravec, Matthew L; Baraniuk, Richard G; Mittleman, Daniel M

    2008-05-01

    We describe a novel, high-speed pulsed terahertz (THz) Fourier imaging system based on compressed sensing (CS), a new signal processing theory, which allows image reconstruction with fewer samples than traditionally required. Using CS, we successfully reconstruct a 64 x 64 image of an object with pixel size 1.4 mm using a randomly chosen subset of the 4096 pixels, which defines the image in the Fourier plane, and observe improved reconstruction quality when we apply phase correction. For our chosen image, only about 12% of the pixels are required for reassembling the image. In combination with phase retrieval, our system has the capability to reconstruct images with only a small subset of Fourier amplitude measurements and thus has potential application in THz imaging with cw sources.

  12. Detecting Thin Cirrus in Multiangle Imaging Spectroradiometer Aerosol Retrievals

    NASA Technical Reports Server (NTRS)

    Pierce, Jeffrey R.; Kahn, Ralph A.; Davis, Matt R.; Comstock, Jennifer M.

    2010-01-01

    Thin cirrus clouds (optical depth (OD) < 03) are often undetected by standard cloud masking in satellite aerosol retrieval algorithms. However, the Mu]tiangle Imaging Spectroradiometer (MISR) aerosol retrieval has the potential to discriminate between the scattering phase functions of cirrus and aerosols, thus separating these components. Theoretical tests show that MISR is sensitive to cirrus OD within Max{0.05 1 20%l, similar to MISR's sensitivity to aerosol OD, and MISR can distinguish between small and large crystals, even at low latitudes, where the range of scattering angles observed by MISR is smallest. Including just two cirrus components in the aerosol retrieval algorithm would capture typical MISR sensitivity to the natural range of cinus properties; in situations where cirrus is present but the retrieval comparison space lacks these components, the retrieval tends to underestimate OD. Generally, MISR can also distinguish between cirrus and common aerosol types when the proper cirrus and aerosol optical models are included in the retrieval comparison space and total column OD is >-0.2. However, in some cases, especially at low latitudes, cirrus can be mistaken for some combinations of dust and large nonabsorbing spherical aerosols, raising a caution about retrievals in dusty marine regions when cirrus is present. Comparisons of MISR with lidar and Aerosol Robotic Network show good agreement in a majority of the cases, but situations where cirrus clouds have optical depths >0.15 and are horizontally inhomogeneous on spatial scales shorter than 50 km pose difficulties for cirrus retrieval using the MISR standard aerosol algorithm..

  13. Mutual information based feature selection for medical image retrieval

    NASA Astrophysics Data System (ADS)

    Zhi, Lijia; Zhang, Shaomin; Li, Yan

    2018-04-01

    In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

  14. A flower image retrieval method based on ROI feature.

    PubMed

    Hong, An-Xiang; Chen, Gang; Li, Jun-Li; Chi, Zhe-Ru; Zhang, Dan

    2004-07-01

    Flower image retrieval is a very important step for computer-aided plant species recognition. In this paper, we propose an efficient segmentation method based on color clustering and domain knowledge to extract flower regions from flower images. For flower retrieval, we use the color histogram of a flower region to characterize the color features of flower and two shape-based features sets, Centroid-Contour Distance (CCD) and Angle Code Histogram (ACH), to characterize the shape features of a flower contour. Experimental results showed that our flower region extraction method based on color clustering and domain knowledge can produce accurate flower regions. Flower retrieval results on a database of 885 flower images collected from 14 plant species showed that our Region-of-Interest (ROI) based retrieval approach using both color and shape features can perform better than a method based on the global color histogram proposed by Swain and Ballard (1991) and a method based on domain knowledge-driven segmentation and color names proposed by Das et al.(1999).

  15. SKL algorithm based fabric image matching and retrieval

    NASA Astrophysics Data System (ADS)

    Cao, Yichen; Zhang, Xueqin; Ma, Guojian; Sun, Rongqing; Dong, Deping

    2017-07-01

    Intelligent computer image processing technology provides convenience and possibility for designers to carry out designs. Shape analysis can be achieved by extracting SURF feature. However, high dimension of SURF feature causes to lower matching speed. To solve this problem, this paper proposed a fast fabric image matching algorithm based on SURF K-means and LSH algorithm. By constructing the bag of visual words on K-Means algorithm, and forming feature histogram of each image, the dimension of SURF feature is reduced at the first step. Then with the help of LSH algorithm, the features are encoded and the dimension is further reduced. In addition, the indexes of each image and each class of image are created, and the number of matching images is decreased by LSH hash bucket. Experiments on fabric image database show that this algorithm can speed up the matching and retrieval process, the result can satisfy the requirement of dress designers with accuracy and speed.

  16. Phase retrieval of images using Gaussian radial bases.

    PubMed

    Trahan, Russell; Hyland, David

    2013-12-20

    Here, the possibility of a noniterative solution to the phase retrieval problem is explored. A new look is taken at the phase retrieval problem that reveals that knowledge of a diffraction pattern's frequency components is enough to recover the image without projective iterations. This occurs when the image is formed using Gaussian bases that give the convenience of a continuous Fourier transform existing in a compact form where square pixels do not. The Gaussian bases are appropriate when circular apertures are used to detect the diffraction pattern because of their optical transfer functions, as discussed briefly. An algorithm is derived that is capable of recovering an image formed by Gaussian bases from only the Fourier transform's modulus, without background constraints. A practical example is shown.

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

    PubMed Central

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

    2014-01-01

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

  18. Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

    PubMed

    Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

    2018-06-15

    Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

  19. 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.

  20. Research of image retrieval technology based on color feature

    NASA Astrophysics Data System (ADS)

    Fu, Yanjun; Jiang, Guangyu; Chen, Fengying

    2009-10-01

    Recently, with the development of the communication and the computer technology and the improvement of the storage technology and the capability of the digital image equipment, more and more image resources are given to us than ever. And thus the solution of how to locate the proper image quickly and accurately is wanted.The early method is to set up a key word for searching in the database, but now the method has become very difficult when we search much more picture that we need. In order to overcome the limitation of the traditional searching method, content based image retrieval technology was aroused. Now, it is a hot research subject.Color image retrieval is the important part of it. Color is the most important feature for color image retrieval. Three key questions on how to make use of the color characteristic are discussed in the paper: the expression of color, the abstraction of color characteristic and the measurement of likeness based on color. On the basis, the extraction technology of the color histogram characteristic is especially discussed. Considering the advantages and disadvantages of the overall histogram and the partition histogram, a new method based the partition-overall histogram is proposed. The basic thought of it is to divide the image space according to a certain strategy, and then calculate color histogram of each block as the color feature of this block. Users choose the blocks that contain important space information, confirming the right value. The system calculates the distance between the corresponding blocks that users choosed. Other blocks merge into part overall histograms again, and the distance should be calculated. Then accumulate all the distance as the real distance between two pictures. The partition-overall histogram comprehensive utilizes advantages of two methods above, by choosing blocks makes the feature contain more spatial information which can improve performance; the distances between partition-overall histogram

  1. Dynamic "inline" images: context-sensitive retrieval and integration of images into Web documents.

    PubMed

    Kahn, Charles E

    2008-09-01

    Integrating relevant images into web-based information resources adds value for research and education. This work sought to evaluate the feasibility of using "Web 2.0" technologies to dynamically retrieve and integrate pertinent images into a radiology web site. An online radiology reference of 1,178 textual web documents was selected as the set of target documents. The ARRS GoldMiner image search engine, which incorporated 176,386 images from 228 peer-reviewed journals, retrieved images on demand and integrated them into the documents. At least one image was retrieved in real-time for display as an "inline" image gallery for 87% of the web documents. Each thumbnail image was linked to the full-size image at its original web site. Review of 20 randomly selected Collaborative Hypertext of Radiology documents found that 69 of 72 displayed images (96%) were relevant to the target document. Users could click on the "More" link to search the image collection more comprehensively and, from there, link to the full text of the article. A gallery of relevant radiology images can be inserted easily into web pages on any web server. Indexing by concepts and keywords allows context-aware image retrieval, and searching by document title and subject metadata yields excellent results. These techniques allow web developers to incorporate easily a context-sensitive image gallery into their documents.

  2. Using deep learning for content-based medical image retrieval

    NASA Astrophysics Data System (ADS)

    Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

    2017-03-01

    Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

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

    PubMed Central

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

    2014-01-01

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

  4. Image Retrieval using Integrated Features of Binary Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Agarwal, Megha; Maheshwari, R. P.

    2011-12-01

    In this paper a new approach for image retrieval is proposed with the application of binary wavelet transform. This new approach facilitates the feature calculation with the integration of histogram and correlogram features extracted from binary wavelet subbands. Experiments are performed to evaluate and compare the performance of proposed method with the published literature. It is verified that average precision and average recall of proposed method (69.19%, 41.78%) is significantly improved compared to optimal quantized wavelet correlogram (OQWC) [6] (64.3%, 38.00%) and Gabor wavelet correlogram (GWC) [10] (64.1%, 40.6%). All the experiments are performed on Corel 1000 natural image database [20].

  5. Intra-operative registration for image enhanced endoscopic sinus surgery using photo-consistency.

    PubMed

    Chen, Min Si; Gonzalez, Gerardo; Lapeer, Rudy

    2007-01-01

    The purpose of this paper is to present an intensity based algorithm for aligning 2D endoscopic images with virtual images generated from pre-operative 3D data. The proposed algorithm uses photo-consistency as the measurement of similarity between images, provided the illumination is independent from the viewing direction.

  6. Photo CD and Other Digital Imaging Technologies: What's out There and What's It For?

    ERIC Educational Resources Information Center

    Chen, Ching-Chih

    1993-01-01

    Describes Kodak's Photo CD technology and its impact on digital imaging. Color desktop publishing, image processing and preservation, image archival storage, and interactive multimedia development, as well as the equipment, software, and services that make these applications possible, are described. Contact information for developers and…

  7. Interactive classification and content-based retrieval of tissue images

    NASA Astrophysics Data System (ADS)

    Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

    2002-11-01

    We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

  8. Photo-reconnaissance applications of computer processing of images.

    NASA Technical Reports Server (NTRS)

    Billingsley, F. C.

    1971-01-01

    An imaging processing technique is developed for enhancement and calibration of imaging experiments. The technique is shown to be useful not only for the original application but also when applied to images from a wide variety of sources.

  9. The application of similar image retrieval in electronic commerce.

    PubMed

    Hu, YuPing; Yin, Hua; Han, Dezhi; Yu, Fei

    2014-01-01

    Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system.

  10. The Application of Similar Image Retrieval in Electronic Commerce

    PubMed Central

    Hu, YuPing; Yin, Hua; Han, Dezhi; Yu, Fei

    2014-01-01

    Traditional online shopping platform (OSP), which searches product information by keywords, faces three problems: indirect search mode, large search space, and inaccuracy in search results. For solving these problems, we discuss and research the application of similar image retrieval in electronic commerce. Aiming at improving the network customers' experience and providing merchants with the accuracy of advertising, we design a reasonable and extensive electronic commerce application system, which includes three subsystems: image search display subsystem, image search subsystem, and product information collecting subsystem. This system can provide seamless connection between information platform and OSP, on which consumers can automatically and directly search similar images according to the pictures from information platform. At the same time, it can be used to provide accuracy of internet marketing for enterprises. The experiment shows the efficiency of constructing the system. PMID:24883411

  11. WFIRST: Retrieval Studies of Directly Imaged Extrasolar Giant Planets

    NASA Astrophysics Data System (ADS)

    Marley, Mark; Lupu, Roxana; Lewis, Nikole K.; WFIRST Coronagraph SITs

    2018-01-01

    The typical direct imaging and spectroscopy target for the WFIRST Coronagraph will be a mature Jupiter-mass giant planet at a few AU from an FGK star. The spectra of such planets is expected to be shaped primarily by scattering from H2O clouds and absorption by gaseous NH3 and CH4. We have computed forward model spectra of such typical planets and applied noise models to understand the quality of photometry and spectra we can expect. Using such simulated datasets we have conducted Markov Chain Monte Carlo and MultiNest retrievals to derive atmospheric abundance of CH4, cloud scattering properties, gravity, and other parameters for various planets and observing modes. Our focus has primarily been to understand which combinations of photometry and spectroscopy at what SNR allow retrievals of atmospheric methane mixing ratios to within a factor of ten of the true value. This is a challenging task for directly imaged planets as the planet mass and radius--and thus surface gravity--are not as well constrained as in the case of transiting planets. We find that for plausible planets and datasets of the quality expected to be obtained by WFIRST it should be possible to place such constraints, at least for some planets. We present some examples of our retrieval results and explain how they have been utilized to help set design requirements on the coronagraph camera and integrated field spectrometer.

  12. Content-based histopathology image retrieval using CometCloud.

    PubMed

    Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

    2014-08-26

    The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two

  13. Generation of high-dynamic range image from digital photo

    NASA Astrophysics Data System (ADS)

    Wang, Ying; Potemin, Igor S.; Zhdanov, Dmitry D.; Wang, Xu-yang; Cheng, Han

    2016-10-01

    A number of the modern applications such as medical imaging, remote sensing satellites imaging, virtual prototyping etc use the High Dynamic Range Image (HDRI). Generally to obtain HDRI from ordinary digital image the camera is calibrated. The article proposes the camera calibration method based on the clear sky as the standard light source and takes sky luminance from CIE sky model for the corresponding geographical coordinates and time. The article considers base algorithms for getting real luminance values from ordinary digital image and corresponding programmed implementation of the algorithms. Moreover, examples of HDRI reconstructed from ordinary images illustrate the article.

  14. Rotation invariant deep binary hashing for fast image retrieval

    NASA Astrophysics Data System (ADS)

    Dai, Lai; Liu, Jianming; Jiang, Aiwen

    2017-07-01

    In this paper, we study how to compactly represent image's characteristics for fast image retrieval. We propose supervised rotation invariant compact discriminative binary descriptors through combining convolutional neural network with hashing. In the proposed network, binary codes are learned by employing a hidden layer for representing latent concepts that dominate on class labels. A loss function is proposed to minimize the difference between binary descriptors that describe reference image and the rotated one. Compared with some other supervised methods, the proposed network doesn't have to require pair-wised inputs for binary code learning. Experimental results show that our method is effective and achieves state-of-the-art results on the CIFAR-10 and MNIST datasets.

  15. Image processing with the radial Hilbert transform of photo-thermal imaging for carious detection

    NASA Astrophysics Data System (ADS)

    El-Sharkawy, Yasser H.

    2014-03-01

    Knowledge of heat transfer in biological bodies has many diagnostic and therapeutic applications involving either raising or lowering of temperature, and often requires precise monitoring of the spatial distribution of thermal histories that are produced during a treatment protocol. The present paper therefore aims to design and implementation of laser therapeutic and imaging system used for carious tracking and drilling by develop a mathematical algorithm using Hilbert transform for edge detection of photo-thermal imaging. photothermal imaging has the ability to penetrate and yield information about an opaque medium well beyond the range of conventional optical imaging. Owing to this ability, Q- switching Nd:YAG laser at wavelength 1064 nm has been extensively used in human teeth to study the sub-surface deposition of laser radiation. The high absorption coefficient of the carious rather than normal region rise its temperature generating IR thermal radiation captured by high resolution thermal camera. Changing the pulse repetition frequency of the laser pulses affects the penetration depth of the laser, which can provide three-dimensional (3D) images in arbitrary planes and allow imaging deep within a solid tissue.

  16. Aerosol retrieval for APEX airborne imaging spectrometer: a preliminary analysis

    NASA Astrophysics Data System (ADS)

    Seidel, Felix; Nieke, Jens; Schläpfer, Daniel; Höller, Robert; von Hoyningen-Huene, Wolfgang; Itten, Klaus

    2005-10-01

    In order to achieve quantitative measurements of the Earth's surface radiance and reflectance, it is important to determine the aerosol optical thickness (AOT) to correct for the optical influence of atmospheric particles. An advanced method for aerosol detection and quantification is required, which is not strongly dependant on disturbing effects due to surface reflectance, gas absorption and Rayleigh scattering features. A short review of existing applicable methods to the APEX airborne imaging spectrometer (380nm to 2500nm), leads to the suggested aerosol retrieval method here in this paper. It will measure the distinct radiance change between two near-UV spectral bands (385nm & 412nm) due to aerosol induced scattering and absorption features. Atmospheric radiation transfer model calculations have been used to analyze the AOT retrieval capability and accuracy of APEX. The noise-equivalent differential AOT is presented along with the retrieval sensitivity to various input variables. It is shown, that the suggested method will be able to identify different aerosol model types and measure AOT and columnar size distribution. The proposed accurate AOT determination will lead to a unique opportunity of two-dimensional pixel-wise mapping of aerosol properties at a high spatial resolution. This will be helpful especially for regional climate studies, atmospheric pollution monitoring and for the improvement of aerosol dispersion models and the validation of aerosol algorithms on spaceborne sensors.

  17. Robust image retrieval from noisy inputs using lattice associative memories

    NASA Astrophysics Data System (ADS)

    Urcid, Gonzalo; Nieves-V., José Angel; García-A., Anmi; Valdiviezo-N., Juan Carlos

    2009-02-01

    Lattice associative memories also known as morphological associative memories are fully connected feedforward neural networks with no hidden layers, whose computation at each node is carried out with lattice algebra operations. These networks are a relatively recent development in the field of associative memories that has proven to be an alternative way to work with sets of pattern pairs for which the storage and retrieval stages use minimax algebra. Different associative memory models have been proposed to cope with the problem of pattern recall under input degradations, such as occlusions or random noise, where input patterns can be composed of binary or real valued entries. In comparison to these and other artificial neural network memories, lattice algebra based memories display better performance for storage and recall capability; however, the computational techniques devised to achieve that purpose require additional processing or provide partial success when inputs are presented with undetermined noise levels. Robust retrieval capability of an associative memory model is usually expressed by a high percentage of perfect recalls from non-perfect input. The procedure described here uses noise masking defined by simple lattice operations together with appropriate metrics, such as the normalized mean squared error or signal to noise ratio, to boost the recall performance of either the min or max lattice auto-associative memories. Using a single lattice associative memory, illustrative examples are given that demonstrate the enhanced retrieval of correct gray-scale image associations from inputs corrupted with random noise.

  18. Storage and retrieval of medical images from data warehouses

    NASA Astrophysics Data System (ADS)

    Tikekar, Rahul V.; Fotouhi, Farshad A.; Ragan, Don P.

    1995-11-01

    As our applications continue to become more sophisticated, the demand for more storage continues to rise. Hence many businesses are looking toward data warehousing technology to satisfy their storage needs. A warehouse is different from a conventional database and hence deserves a different approach while storing data that might be retrieved at a later point in time. In this paper we look at the problem of storing and retrieving medical image data from a warehouse. We regard the warehouse as a pyramid with fast storage devices at the top and slower storage devices at the bottom. Our approach is to store the most needed information abstract at the top of the pyramid and more detailed and storage consuming data toward the end of the pyramid. This information is linked for browsing purposes. In a similar fashion, during the retrieval of data, the user is given a sample representation with browse option of the detailed data and, as required, more and more details are made available.

  19. Organic non-volatile resistive photo-switches for flexible image detector arrays.

    PubMed

    Nau, Sebastian; Wolf, Christoph; Sax, Stefan; List-Kratochvil, Emil J W

    2015-02-01

    A unique implementation of an organic image detector using resistive photo-switchable pixels is presented. This resistive photo-switch comprises the vertical integration of an organic photodiode and an organic resistive switching memory element. The photodiodes act as a photosensitive element while the resistive switching elements simultaneously store the detected light information. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. 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.

  1. Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows the Los Angeles basin. The area's freeways are visible as dark lines. The Los Angles harbor breakwater off Long Beach is seen as a bright line. Vessels in the harbor show as bright points.

  2. Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Photos of earth observations taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows Lake Okeechobee (right) and Lake Istokopoga (left) in Central Florida. Lake Okeechobee is bounded on the east by rectangular agricultural fields and to the south and west by swamps and wetlands which appear as bright features.

  3. Content-based image retrieval with ontological ranking

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

  4. The World Bank Photo Library. A Report on Classification, Indexing, and Retrieval of Slide Collection; Organization and Circulation of Visual Materials and Matters Relating to Photo Library Administration.

    ERIC Educational Resources Information Center

    Bikshapathi, Adepu

    The World Bank, a specialized agency of the United Nations, is devoted to promoting the economic development of its member nations. Its photo library, with a collection of nearly 25,000 black-and-white photographs and color slides, serves as a resource center for various activities of the Bank and other organizations. Intended as a background…

  5. Retrieving Coherent Receiver Function Images with Dense Arrays

    NASA Astrophysics Data System (ADS)

    Zhong, M.; Zhan, Z.

    2016-12-01

    Receiver functions highlight converted phases (e.g., Ps, PpPs, sP) and have been widely used to study seismic interfaces. With a dense array, receiver functions (RFs) at multiple stations form a RF image that can provide more robust/detailed constraints. However, due to noise in data, non-uniqueness of deconvolution, and local structures that cannot be detected across neighboring stations, traditional RF images are often noisy and hard to interpret. Previous attempts to enhance coherence by stacking RFs from multiple events or post-filtering the RF images have not produced satisfactory improvements. Here, we propose a new method to retrieve coherent RF images with dense arrays. We take advantage of the waveform coherency at neighboring stations and invert for a small number of coherent arrivals for their RFs. The new RF images contain only the coherent arrivals required to fit data well. Synthetic tests and preliminary applications on real data demonstrate that the new RF images are easier to interpret and improve our ability to infer Earth structures using receiver functions.

  6. Searching for Images: The Analysis of Users' Queries for Image Retrieval in American History.

    ERIC Educational Resources Information Center

    Choi, Youngok; Rasmussen, Edie M.

    2003-01-01

    Studied users' queries for visual information in American history to identify the image attributes important for retrieval and the characteristics of users' queries for digital images, based on queries from 38 faculty and graduate students. Results of pre- and post-test questionnaires and interviews suggest principle categories of search terms.…

  7. 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.

  8. Medical Image Retrieval Using Multi-Texton Assignment.

    PubMed

    Tang, Qiling; Yang, Jirong; Xia, Xianfu

    2018-02-01

    In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation. We investigate the effects of different parameters on system performance in order to choose the appropriate ones for our datasets and carry out experiments on the IRMA-2009 medical collection and the mammographic patch dataset. The extensive experimental results demonstrate that the proposed method has superior performance.

  9. Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

    PubMed

    Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

    2015-03-09

    Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

  10. Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

    NASA Astrophysics Data System (ADS)

    Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

    2015-03-01

    Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

  11. Photo-reconnaissance applications of computer processing of images.

    NASA Technical Reports Server (NTRS)

    Billingsley, F. C.

    1972-01-01

    Discussion of imaging processing techniques for enhancement and calibration of Jet Propulsion Laboratory imaging experiment pictures returned from NASA space vehicles such as Ranger, Mariner and Surveyor. Particular attention is given to data transmission, resolution vs recognition, and color aspects of digital data processing. The effectiveness of these techniques in applications to images from a wide variety of sources is noted. It is anticipated that the use of computer processing for enhancement of imagery will increase with the improvement and cost reduction of these techniques in the future.

  12. Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

    PubMed

    Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

    2014-01-01

    Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

  13. 78 FR 16707 - Certain Digital Photo Frames and Image Display Devices and Components Thereof; Issuance of a...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-18

    ... Image Display Devices and Components Thereof; Issuance of a Limited Exclusion Order and Cease and Desist... within the United States after importation of certain digital photo frames and image display devices and...: (1) The unlicensed entry of digital photo frames and image display devices and components thereof...

  14. 76 FR 59737 - In the Matter of Certain Digital Photo Frames and Image Display Devices and Components Thereof...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-09-27

    ... Frames and Image Display Devices and Components Thereof; Notice of Institution of Investigation... United States after importation of certain digital photo frames and image display devices and components... certain digital photo frames and image display devices and components thereof that infringe one or more of...

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

    USDA-ARS?s Scientific Manuscript database

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

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

    NASA Astrophysics Data System (ADS)

    Strupp-Adams, Annette; Henderson, Earl

    1999-12-01

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

  17. 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

  18. Coupled binary embedding for large-scale image retrieval.

    PubMed

    Zheng, Liang; Wang, Shengjin; Tian, Qi

    2014-08-01

    Visual matching is a crucial step in image retrieval based on the bag-of-words (BoW) model. In the baseline method, two keypoints are considered as a matching pair if their SIFT descriptors are quantized to the same visual word. However, the SIFT visual word has two limitations. First, it loses most of its discriminative power during quantization. Second, SIFT only describes the local texture feature. Both drawbacks impair the discriminative power of the BoW model and lead to false positive matches. To tackle this problem, this paper proposes to embed multiple binary features at indexing level. To model correlation between features, a multi-IDF scheme is introduced, through which different binary features are coupled into the inverted file. We show that matching verification methods based on binary features, such as Hamming embedding, can be effectively incorporated in our framework. As an extension, we explore the fusion of binary color feature into image retrieval. The joint integration of the SIFT visual word and binary features greatly enhances the precision of visual matching, reducing the impact of false positive matches. Our method is evaluated through extensive experiments on four benchmark datasets (Ukbench, Holidays, DupImage, and MIR Flickr 1M). We show that our method significantly improves the baseline approach. In addition, large-scale experiments indicate that the proposed method requires acceptable memory usage and query time compared with other approaches. Further, when global color feature is integrated, our method yields competitive performance with the state-of-the-arts.

  19. [PACS: storage and retrieval of digital radiological image data].

    PubMed

    Wirth, S; Treitl, M; Villain, S; Lucke, A; Nissen-Meyer, S; Mittermaier, I; Pfeifer, K-J; Reiser, M

    2005-08-01

    Efficient handling of both picture archiving and retrieval is a crucial factor when new PACS installations as well as technical upgrades are planned. For a large PACS installation for 200 actual studies, the number, modality,and body region of available priors were evaluated. In addition, image access time of 100 CT studies from hard disk (RAID), magneto-optic disk (MOD), and tape archives (TAPE) were accessed. For current examinations priors existed in 61.1% with an averaged quantity of 7.7 studies. Thereof 56.3% were within 0-3 months, 84.9% within 12 months, 91.7% within 24 months, and 96.2% within 36 months. On average, access to images from the hard disk cache was more than 100 times faster then from MOD or TAPE. Since only PACS RAID provides online image access, at least current imaging of the past 12 months should be available from cache. An accurate prefetching mechanism facilitates effective use of the expensive online cache area. For that, however, close interaction of PACS, RIS, and KIS is an indispensable prerequisite.

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

    PubMed

    Sivakamasundari, J; Natarajan, V

    2015-01-01

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

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

    ERIC Educational Resources Information Center

    Makovoz, Gennadiy

    2010-01-01

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

  2. Digital image processing for photo-reconnaissance applications

    NASA Technical Reports Server (NTRS)

    Billingsley, F. C.

    1972-01-01

    Digital image-processing techniques developed for processing pictures from NASA space vehicles are analyzed in terms of enhancement, quantitative restoration, and information extraction. Digital filtering, and the action of a high frequency filter in the real and Fourier domain are discussed along with color and brightness.

  3. Study report on laser storage and retrieval of image data

    NASA Technical Reports Server (NTRS)

    Becker, C. H.

    1976-01-01

    The theoretical foundation is presented for a system of real-time nonphotographic and nonmagnetic digital laser storage and retrieval of image data. The system utilizes diffraction-limited laser focusing upon thin metal films, melting elementary holes in the metal films in laser focus. The metal films are encapsulated in rotating flexible mylar discs which act as the permanent storage carries. Equal sized holes encompass two dimensional digital ensembles of information bits which are time-sequentially (bit by bit) stored and retrieved. The bits possess the smallest possible size, defined by the Rayleigh criterion of coherent physical optics. Space and time invariant reflective read-out of laser discs with a small laser, provides access to the stored digital information. By eliminating photographic and magnetic data processing, which characterize the previous state of the art, photographic grain, diffusion, and gamma-distortion do not exist. Similarly, magnetic domain structures, magnetic gaps, and magnetic read-out are absent with a digital laser disc system.

  4. The element of naturalness when evaluating image quality of digital photo documentation after sexual assault.

    PubMed

    Ernst, E J; Speck, P M; Fitzpatrick, J J

    2012-01-01

    Digital photography is a valuable adjunct to document physical injuries after sexual assault. In order for a digital photograph to have high image quality, there must exist a high level of naturalness. Digital photo documentation has varying degrees of naturalness; however, for a photograph to be natural, specific technical elements for the viewer must be satisfied. No tool was available to rate the naturalness of digital photo documentation of female genital injuries after sexual assault. The Photo Documentation Image Quality Scoring System (PDIQSS) tool was developed to rate technical elements for naturalness. Using this tool, experts evaluated randomly selected digital photographs of female genital injuries captured following sexual assault. Naturalness of female genital injuries following sexual assault was demonstrated when measured in all dimensions.

  5. Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

    PubMed

    Bidgood, W D; Bray, B; Brown, N; Mori, A R; Spackman, K A; Golichowski, A; Jones, R H; Korman, L; Dove, B; Hildebrand, L; Berg, M

    1999-01-01

    To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries.

  6. Content-based image retrieval applied to bone age assessment

    NASA Astrophysics Data System (ADS)

    Fischer, Benedikt; Brosig, André; Welter, Petra; Grouls, Christoph; Günther, Rolf W.; Deserno, Thomas M.

    2010-03-01

    Radiological bone age assessment is based on local image regions of interest (ROI), such as the epiphysis or the area of carpal bones. These are compared to a standardized reference and scores determining the skeletal maturity are calculated. For computer-aided diagnosis, automatic ROI extraction and analysis is done so far mainly by heuristic approaches. Due to high variations in the imaged biological material and differences in age, gender and ethnic origin, automatic analysis is difficult and frequently requires manual interactions. On the contrary, epiphyseal regions (eROIs) can be compared to previous cases with known age by content-based image retrieval (CBIR). This requires a sufficient number of cases with reliable positioning of the eROI centers. In this first approach to bone age assessment by CBIR, we conduct leaving-oneout experiments on 1,102 left hand radiographs and 15,428 metacarpal and phalangeal eROIs from the USC hand atlas. The similarity of the eROIs is assessed by cross-correlation of 16x16 scaled eROIs. The effects of the number of eROIs, two age computation methods as well as the number of considered CBIR references are analyzed. The best results yield an error rate of 1.16 years and a standard deviation of 0.85 years. As the appearance of the hand varies naturally by up to two years, these results clearly demonstrate the applicability of the CBIR approach for bone age estimation.

  7. Psychophysical experiments on the PicHunter image retrieval system

    NASA Astrophysics Data System (ADS)

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

    2001-01-01

    Psychophysical experiments were conducted on PicHunter, a content-based image retrieval (CBIR) experimental prototype with the following properties: (1) Based on a model of how users respond, it uses Bayes's rule to predict what target users want, given their actions. (2) It possesses an extremely simple user interface. (3) It employs an entropy- based scheme to improve convergence. (4) It introduces a paradigm for assessing the performance of CBIR systems. Experiments 1-3 studied human judgment of image similarity to obtain data for the model. Experiment 4 studied the importance of using: (a) semantic information, (b) memory of earlier input, and (c) relative and absolute judgments of similarity. Experiment 5 tested an approach that we propose for comparing performances of CBIR systems objectively. Finally, experiment 6 evaluated the most informative display-updating scheme that is based on entropy minimization, and confirmed earlier simulation results. These experiments represent one of the first attempts to quantify CBIR performance based on psychophysical studies, and they provide valuable data for improving CBIR algorithms. Even though they were designed with PicHunter in mind, their results can be applied to any CBIR system and, more generally, to any system that involves judgment of image similarity by humans.

  8. Prototypes for Content-Based Image Retrieval in Clinical Practice

    PubMed Central

    Depeursinge, Adrien; Fischer, Benedikt; Müller, Henning; Deserno, Thomas M

    2011-01-01

    Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice. We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word “retrieval” in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems. In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently. In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice. PMID:21892374

  9. Ontology of gaps in content-based image retrieval.

    PubMed

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

    2009-04-01

    Content-based image retrieval (CBIR) is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). CBIR has a potential for making a strong impact in diagnostics, research, and education. Research as reported in the scientific literature, however, has not made significant inroads as medical CBIR applications incorporated into routine clinical medicine or medical research. The cause is often attributed (without supporting analysis) to the inability of these applications in overcoming the "semantic gap." The semantic gap divides the high-level scene understanding and interpretation available with human cognitive capabilities from the low-level pixel analysis of computers, based on mathematical processing and artificial intelligence methods. In this paper, we suggest a more systematic and comprehensive view of the concept of "gaps" in medical CBIR research. In particular, we define an ontology of 14 gaps that addresses the image content and features, as well as system performance and usability. In addition to these gaps, we identify seven system characteristics that impact CBIR applicability and performance. The framework we have created can be used a posteriori to compare medical CBIR systems and approaches for specific biomedical image domains and goals and a priori during the design phase of a medical CBIR application, as the systematic analysis of gaps provides detailed insight in system comparison and helps to direct future research.

  10. Evaluation of image quality of digital photo documentation of female genital injuries following sexual assault.

    PubMed

    Ernst, E J; Speck, Patricia M; Fitzpatrick, Joyce J

    2011-12-01

    With the patient's consent, physical injuries sustained in a sexual assault are evaluated and treated by the sexual assault nurse examiner (SANE) and documented on preprinted traumagrams and with photographs. Digital imaging is now available to the SANE for documentation of sexual assault injuries, but studies of the image quality of forensic digital imaging of female genital injuries after sexual assault were not found in the literature. The Photo Documentation Image Quality Scoring System (PDIQSS) was developed to rate the image quality of digital photo documentation of female genital injuries after sexual assault. Three expert observers performed evaluations on 30 separate images at two points in time. An image quality score, the sum of eight integral technical and anatomical attributes on the PDIQSS, was obtained for each image. Individual image quality ratings, defined by rating image quality for each of the data, were also determined. The results demonstrated a high level of image quality and agreement when measured in all dimensions. For the SANE in clinical practice, the results of this study indicate that a high degree of agreement exists between expert observers when using the PDIQSS to rate image quality of individual digital photographs of female genital injuries after sexual assault. © 2011 International Association of Forensic Nurses.

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

    PubMed

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

    2014-03-01

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

  12. BIRAM: a content-based image retrieval framework for medical images

    NASA Astrophysics Data System (ADS)

    Moreno, Ramon A.; Furuie, Sergio S.

    2006-03-01

    In the medical field, digital images are becoming more and more important for diagnostics and therapy of the patients. At the same time, the development of new technologies has increased the amount of image data produced in a hospital. This creates a demand for access methods that offer more than text-based queries for retrieval of the information. In this paper is proposed a framework for the retrieval of medical images that allows the use of different algorithms for the search of medical images by similarity. The framework also enables the search for textual information from an associated medical report and DICOM header information. The proposed system can be used for support of clinical decision making and is intended to be integrated with an open source picture, archiving and communication systems (PACS). The BIRAM has the following advantages: (i) Can receive several types of algorithms for image similarity search; (ii) Allows the codification of the report according to a medical dictionary, improving the indexing of the information and retrieval; (iii) The algorithms can be selectively applied to images with the appropriated characteristics, for instance, only in magnetic resonance images. The framework was implemented in Java language using a MS Access 97 database. The proposed framework can still be improved, by the use of regions of interest (ROI), indexing with slim-trees and integration with a PACS Server.

  13. Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach.

    PubMed

    Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu

    2017-06-30

    This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.

  14. Computer screen photo-excited surface plasmon resonance imaging.

    PubMed

    Filippini, Daniel; Winquist, Fredrik; Lundström, Ingemar

    2008-09-12

    Angle and spectra resolved surface plasmon resonance (SPR) images of gold and silver thin films with protein deposits is demonstrated using a regular computer screen as light source and a web camera as detector. The screen provides multiple-angle illumination, p-polarized light and controlled spectral radiances to excite surface plasmons in a Kretchmann configuration. A model of the SPR reflectances incorporating the particularities of the source and detector explain the observed signals and the generation of distinctive SPR landscapes is demonstrated. The sensitivity and resolution of the method, determined in air and solution, are 0.145 nm pixel(-1), 0.523 nm, 5.13x10(-3) RIU degree(-1) and 6.014x10(-4) RIU, respectively, encouraging results at this proof of concept stage and considering the ubiquity of the instrumentation.

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

    PubMed

    Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore

    2011-01-01

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

  16. Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows a 50 by 120 kilometer (30 by 75 mile) area of the Mediterranean Sea and the eastern coast of Central Sardinia (left). The city of Arbatose is seen as a bright area along the coast in the lower part of the image, and the star-like spot off the coast is a ship's reflection. The Gulf of Orsei is near the top of the image. Bright, mottled features in the sea (right) represent surface choppiness.

  17. Forensic use of photo response non-uniformity of imaging sensors and a counter method.

    PubMed

    Dirik, Ahmet Emir; Karaküçük, Ahmet

    2014-01-13

    Analogous to use of bullet scratches in forensic science, the authenticity of a digital image can be verified through the noise characteristics of an imaging sensor. In particular, photo-response non-uniformity noise (PRNU) has been used in source camera identification (SCI). However, this technique can be used maliciously to track or inculpate innocent people. To impede such tracking, PRNU noise should be suppressed significantly. Based on this motivation, we propose a counter forensic method to deceive SCI. Experimental results show that it is possible to impede PRNU-based camera identification for various imaging sensors while preserving the image quality.

  18. Image, word, action: interpersonal dynamics in a photo-sharing community.

    PubMed

    Suler, John

    2008-10-01

    In online photo-sharing communities, the individual's expression of self and the relationships that evolve among members is determined by the kinds of images that are shared, by the words exchanged among members, and by interpersonal actions that do not specifically rely on images or text. This article examines the dynamics of personal expression via images in Flickr, including a proposed system for identifying the dimensions of imagistic communication and a discussion of the psychological meanings embedded in a sequence of images. It explores how photographers use text descriptors to supplement their images and how different types of comments on photographs influence interpersonal relationships. The "fav"--when members choose an image as one of their favorites--is examined as one type of action that can serve a variety of interpersonal functions. Although images play a powerful role in the expression of self, it is the integration of images, words, and actions that maximize the development of relationships.

  19. Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

    NASA Technical Reports Server (NTRS)

    Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr; hide

    2015-01-01

    A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

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

    ERIC Educational Resources Information Center

    Wang, James Z.; Du, Yanping

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

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

    PubMed

    Balan, J A Alex Rajju; Rajan, S Edward

    2014-01-01

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

  2. Leveraging Terminologies for Retrieval of Radiology Reports with Critical Imaging Findings

    PubMed Central

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

    2011-01-01

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

  3. Web image retrieval using an effective topic and content-based technique

    NASA Astrophysics Data System (ADS)

    Lee, Ching-Cheng; Prabhakara, Rashmi

    2005-03-01

    There has been an exponential growth in the amount of image data that is available on the World Wide Web since the early development of Internet. With such a large amount of information and image available and its usefulness, an effective image retrieval system is thus greatly needed. In this paper, we present an effective approach with both image matching and indexing techniques that improvise on existing integrated image retrieval methods. This technique follows a two-phase approach, integrating query by topic and query by example specification methods. In the first phase, The topic-based image retrieval is performed by using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. This technique consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. In the second phase, we use query by example specification to perform a low-level content-based image match in order to retrieve smaller and relatively closer results of the example image. From this, information related to the image feature is automatically extracted from the query image. The main objective of our approach is to develop a functional image search and indexing technique and to demonstrate that better retrieval results can be achieved.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  5. Feasibility test of a solid state spin-scan photo-imaging system

    NASA Technical Reports Server (NTRS)

    Laverty, N. P.

    1973-01-01

    The feasibility of using a solid-state photo-imaging system to obtain resolution imagery from a Pioneer-type spinning spacecraft in future exploratory missions to the outer planets is discussed. Evaluation of the photo-imaging system performance, based on electrical video signal analysis recorded on magnetic tape, shows that the signal-to-noise (S/N) ratios obtained at low spatial frequencies exceed the anticipated performance and that measured modulation transfer functions exhibited some degradation in comparison with the estimated values, primarily owing to the difficulty in obtaining a precise focus of the optical system in the laboratory with the test patterns in close proximity to the objective lens. A preliminary flight model design of the photo-imaging system is developed based on the use of currently available phototransistor arrays. Image quality estimates that will be obtained are presented in terms of S/N ratios and spatial resolution for the various planets and satellites. Parametric design tradeoffs are also defined.

  6. Structural texture similarity metrics for image analysis and retrieval.

    PubMed

    Zujovic, Jana; Pappas, Thrasyvoulos N; Neuhoff, David L

    2013-07-01

    We develop new metrics for texture similarity that accounts for human visual perception and the stochastic nature of textures. The metrics rely entirely on local image statistics and allow substantial point-by-point deviations between textures that according to human judgment are essentially identical. The proposed metrics extend the ideas of structural similarity and are guided by research in texture analysis-synthesis. They are implemented using a steerable filter decomposition and incorporate a concise set of subband statistics, computed globally or in sliding windows. We conduct systematic tests to investigate metric performance in the context of "known-item search," the retrieval of textures that are "identical" to the query texture. This eliminates the need for cumbersome subjective tests, thus enabling comparisons with human performance on a large database. Our experimental results indicate that the proposed metrics outperform peak signal-to-noise ratio (PSNR), structural similarity metric (SSIM) and its variations, as well as state-of-the-art texture classification metrics, using standard statistical measures.

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

    NASA Astrophysics Data System (ADS)

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

    2018-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2001-05-01

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

  12. Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). This image shows a 50 by 100 kilometer (30 by 60 mile) area of the Imperial Valley in Southern California and neighboring Mexico. The checkered patterns represent agricultural fields where different types of crops in different stages of growth are cultivated. The very bright areas are (top left to lower right) the U.S. towns of Brawley, Imperial, El Centro, Calexico and the Mexican city of Mexicali. The bright L-shaped line (upper right) is the All-American water canal.

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

    PubMed

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

    2018-01-25

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

  14. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    NASA Astrophysics Data System (ADS)

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-02-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  15. Fundus Image Features Extraction for Exudate Mining in Coordination with Content Based Image Retrieval: A Study

    NASA Astrophysics Data System (ADS)

    Gururaj, C.; Jayadevappa, D.; Tunga, Satish

    2018-06-01

    Medical field has seen a phenomenal improvement over the previous years. The invention of computers with appropriate increase in the processing and internet speed has changed the face of the medical technology. However there is still scope for improvement of the technologies in use today. One of the many such technologies of medical aid is the detection of afflictions of the eye. Although a repertoire of research has been accomplished in this field, most of them fail to address how to take the detection forward to a stage where it will be beneficial to the society at large. An automated system that can predict the current medical condition of a patient after taking the fundus image of his eye is yet to see the light of the day. Such a system is explored in this paper by summarizing a number of techniques for fundus image features extraction, predominantly hard exudate mining, coupled with Content Based Image Retrieval to develop an automation tool. The knowledge of the same would bring about worthy changes in the domain of exudates extraction of the eye. This is essential in cases where the patients may not have access to the best of technologies. This paper attempts at a comprehensive summary of the techniques for Content Based Image Retrieval (CBIR) or fundus features image extraction, and few choice methods of both, and an exploration which aims to find ways to combine these two attractive features, and combine them so that it is beneficial to all.

  16. 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

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

    PubMed

    Kahn, Charles E; Rubin, Daniel L

    2009-01-01

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

  18. Automated Semantic Indexing of Figure Captions to Improve Radiology Image Retrieval

    PubMed Central

    Kahn, Charles E.; Rubin, Daniel L.

    2009-01-01

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

  19. Semantics of User Interface for Image Retrieval: Possibility Theory and Learning Techniques.

    ERIC Educational Resources Information Center

    Crehange, M.; And Others

    1989-01-01

    Discusses the need for a rich semantics for the user interface in interactive image retrieval and presents two methods for building such interfaces: possibility theory applied to fuzzy data retrieval, and a machine learning technique applied to learning the user's deep need. Prototypes developed using videodisks and knowledge-based software are…

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

    PubMed

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

    2017-03-01

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

  1. Extending the fundamental imaging-depth limit of multi-photon microscopy by imaging with photo-activatable fluorophores.

    PubMed

    Chen, Zhixing; Wei, Lu; Zhu, Xinxin; Min, Wei

    2012-08-13

    It is highly desirable to be able to optically probe biological activities deep inside live organisms. By employing a spatially confined excitation via a nonlinear transition, multiphoton fluorescence microscopy has become indispensable for imaging scattering samples. However, as the incident laser power drops exponentially with imaging depth due to scattering loss, the out-of-focus fluorescence eventually overwhelms the in-focal signal. The resulting loss of imaging contrast defines a fundamental imaging-depth limit, which cannot be overcome by increasing excitation intensity. Herein we propose to significantly extend this depth limit by multiphoton activation and imaging (MPAI) of photo-activatable fluorophores. The imaging contrast is drastically improved due to the created disparity of bright-dark quantum states in space. We demonstrate this new principle by both analytical theory and experiments on tissue phantoms labeled with synthetic caged fluorescein dye or genetically encodable photoactivatable GFP.

  2. Contrast-enhanced magneto-photo-acoustic imaging in vivo using dual-contrast nanoparticles☆

    PubMed Central

    Qu, Min; Mehrmohammadi, Mohammad; Truby, Ryan; Graf, Iulia; Homan, Kimberly; Emelianov, Stanislav

    2014-01-01

    By mapping the distribution of targeted plasmonic nanoparticles (NPs), photoacoustic (PA) imaging offers the potential to detect the pathologies in the early stages. However, optical absorption of the endogenous chromophores in the background tissue significantly reduces the contrast resolution of photoacoustic imaging. Previously, we introduced MPA imaging – a synergistic combination of magneto-motive ultrasound (MMUS) and PA imaging, and demonstrated MPA contrast enhancement using cell culture studies. In the current study, contrast enhancement was investigated in vivo using the magneto-photo-acoustic (MPA) imaging augmented with dual-contrast nanoparticles. Liposomal nanoparticles (LNPs) possessing both optical absorption and magnetic properties were injected into a murine tumor model. First, photoacoustic signals were generated from both the endogenous absorbers in the tissue and the liposomal nanoparticles in the tumor. Then, given significant differences in magnetic properties of tissue and LNPs, the magnetic response of LNPs (i.e. MMUS signal) was utilized to suppress the unwanted PA signals from the background tissue thus improving the PA imaging contrast. In this study, we demonstrated the 3D MPA imaging of LNP-labeled xenografted tumor in a live animal. Compared to conventional PA imaging, the MPA imaging show significantly enhanced contrast between the nanoparticle-labeled tumor and the background tissue. Our results suggest the feasibility of MPA imaging for high contrast in vivo mapping of dual-contrast nanoparticles. PMID:24653976

  3. Tetanus (Lockjaw) Photos

    MedlinePlus

    ... be unsuitable for children. Viewing discretion is advised. Photos of the Disease and Images of People Affected by the Disease This micrograph ... Photo ID# 2857 PHIL Photo ID# 1657 PHIL Photo ID# 6373 Additional Images and Regulations Be sure to see the regulations ...

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2017-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Bouteldja, Samia; Kourgli, Assia

    2017-03-01

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

  7. Contrast-enhanced magneto-photo-acoustic imaging in vivo using dual-contrast nanoparticles.

    PubMed

    Qu, Min; Mehrmohammadi, Mohammad; Truby, Ryan; Graf, Iulia; Homan, Kimberly; Emelianov, Stanislav

    2014-06-01

    By mapping the distribution of targeted plasmonic nanoparticles (NPs), photoacoustic (PA) imaging offers the potential to detect the pathologies in the early stages. However, optical absorption of the endogenous chromophores in the background tissue significantly reduces the contrast resolution of photoacoustic imaging. Previously, we introduced MPA imaging - a synergistic combination of magneto-motive ultrasound (MMUS) and PA imaging, and demonstrated MPA contrast enhancement using cell culture studies. In the current study, contrast enhancement was investigated in vivo using the magneto-photo-acoustic (MPA) imaging augmented with dual-contrast nanoparticles. Liposomal nanoparticles (LNPs) possessing both optical absorption and magnetic properties were injected into a murine tumor model. First, photoacoustic signals were generated from both the endogenous absorbers in the tissue and the liposomal nanoparticles in the tumor. Then, given significant differences in magnetic properties of tissue and LNPs, the magnetic response of LNPs (i.e. MMUS signal) was utilized to suppress the unwanted PA signals from the background tissue and thus improves the PA imaging contrast. In this study, we demonstrated the 3D MPA image of LNP-labeled xenografted tumor in a live animal. Compared to conventional PA imaging, the MPA images show significantly enhanced contrast between the nanoparticle-labeled tumor and the background tissue. Our results suggest the feasibility of MPA for high contrast in vivo mapping of dual-contrast nanoparticles.

  8. Using digital photo technology to improve visualization of gastric lumen CT images

    NASA Astrophysics Data System (ADS)

    Pyrgioti, M.; Kyriakidis, A.; Chrysostomou, S.; Panaritis, V.

    2006-12-01

    In order to evaluate the gastric lumen CT images better, a new method is being applied to images using an Image Processing software. During a 12-month period, 69 patients with various gastric symptoms and 20 normal (as far as it concerns the upper gastrointestinal system) volunteers underwent computed tomography of the upper gastrointestinal system. Just before the examination the patients and the normal volunteers underwent preparation with 40 ml soda water and 10 ml gastrografin. All the CT images were digitized with an Olympus 3.2 Mpixel digital camera and further processed with an Image Processing software. The administration per os of gastrografin and soda water resulted in the distension of the stomach and consequently better visualization of all the anatomic parts. By using an Image Processing software in a PC, all the pathological and normal images of the stomach were better diagnostically estimated. We believe that the photo digital technology improves the diagnostic capacity not only of the CT image but also in MRI and probably many other imaging methods.

  9. 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

  10. A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

    NASA Technical Reports Server (NTRS)

    Koshak, William J.

    2009-01-01

    A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

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

    DTIC Science & Technology

    2016-06-01

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

  12. 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.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  15. Evaluation of contents-based image retrieval methods for a database of logos on drug tablets

    NASA Astrophysics Data System (ADS)

    Geradts, Zeno J.; Hardy, Huub; Poortman, Anneke; Bijhold, Jurrien

    2001-02-01

    In this research an evaluation has been made of the different ways of contents based image retrieval of logos of drug tablets. On a database of 432 illicitly produced tablets (mostly containing MDMA), we have compared different retrieval methods. Two of these methods were available from commercial packages, QBIC and Imatch, where the implementation of the contents based image retrieval methods are not exactly known. We compared the results for this database with the MPEG-7 shape comparison methods, which are the contour-shape, bounding box and region-based shape methods. In addition, we have tested the log polar method that is available from our own research.

  16. Near Infrared Fluorescence Imaging in Nano-Therapeutics and Photo-Thermal Evaluation

    PubMed Central

    Vats, Mukti; Mishra, Sumit Kumar; Baghini, Mahdieh Shojaei; Chauhan, Deepak S.; Srivastava, Rohit; De, Abhijit

    2017-01-01

    The unresolved and paramount challenge in bio-imaging and targeted therapy is to clearly define and demarcate the physical margins of tumor tissue. The ability to outline the healthy vital tissues to be carefully navigated with transection while an intraoperative surgery procedure is performed sets up a necessary and under-researched goal. To achieve the aforementioned objectives, there is a need to optimize design considerations in order to not only obtain an effective imaging agent but to also achieve attributes like favorable water solubility, biocompatibility, high molecular brightness, and a tissue specific targeting approach. The emergence of near infra-red fluorescence (NIRF) light for tissue scale imaging owes to the provision of highly specific images of the target organ. The special characteristics of near infra-red window such as minimal auto-fluorescence, low light scattering, and absorption of biomolecules in tissue converge to form an attractive modality for cancer imaging. Imparting molecular fluorescence as an exogenous contrast agent is the most beneficial attribute of NIRF light as a clinical imaging technology. Additionally, many such agents also display therapeutic potentials as photo-thermal agents, thus meeting the dual purpose of imaging and therapy. Here, we primarily discuss molecular imaging and therapeutic potentials of two such classes of materials, i.e., inorganic NIR dyes and metallic gold nanoparticle based materials. PMID:28452928

  17. Optical image encryption via high-quality computational ghost imaging using iterative phase retrieval

    NASA Astrophysics Data System (ADS)

    Liansheng, Sui; Yin, Cheng; Bing, Li; Ailing, Tian; Krishna Asundi, Anand

    2018-07-01

    A novel computational ghost imaging scheme based on specially designed phase-only masks, which can be efficiently applied to encrypt an original image into a series of measured intensities, is proposed in this paper. First, a Hadamard matrix with a certain order is generated, where the number of elements in each row is equal to the size of the original image to be encrypted. Each row of the matrix is rearranged into the corresponding 2D pattern. Then, each pattern is encoded into the phase-only masks by making use of an iterative phase retrieval algorithm. These specially designed masks can be wholly or partially used in the process of computational ghost imaging to reconstruct the original information with high quality. When a significantly small number of phase-only masks are used to record the measured intensities in a single-pixel bucket detector, the information can be authenticated without clear visualization by calculating the nonlinear correlation map between the original image and its reconstruction. The results illustrate the feasibility and effectiveness of the proposed computational ghost imaging mechanism, which will provide an effective alternative for enriching the related research on the computational ghost imaging technique.

  18. Sensing the delivery and endocytosis of nanoparticles using magneto-photo-acoustic imaging

    PubMed Central

    Qu, M.; Mehrmohammadi, M.; Emelianov, S.Y.

    2015-01-01

    Many biomedical applications necessitate a targeted intracellular delivery of the nanomaterial to specific cells. Therefore, a non-invasive and reliable imaging tool is required to detect both the delivery and cellular endocytosis of the nanoparticles. Herein, we demonstrate that magneto-photo-acoustic (MPA) imaging can be used to monitor the delivery and to identify endocytosis of magnetic and optically absorbing nanoparticles. The relationship between photoacoustic (PA) and magneto-motive ultrasound (MMUS) signals from the in vitro samples were analyzed to identify the delivery and endocytosis of nanoparticles. The results indicated that during the delivery of nanoparticles to the vicinity of the cells, both PA and MMUS signals are almost linearly proportional. However, accumulation of nanoparticles within the cells leads to nonlinear MMUS-PA relationship, due to non-linear MMUS signal amplification. Therefore, through longitudinal MPA imaging, it is possible to monitor the delivery of nanoparticles and identify the endocytosis of the nanoparticles by living cells. PMID:26640773

  19. Performance comparison of leading image codecs: H.264/AVC Intra, JPEG2000, and Microsoft HD Photo

    NASA Astrophysics Data System (ADS)

    Tran, Trac D.; Liu, Lijie; Topiwala, Pankaj

    2007-09-01

    This paper provides a detailed rate-distortion performance comparison between JPEG2000, Microsoft HD Photo, and H.264/AVC High Profile 4:4:4 I-frame coding for high-resolution still images and high-definition (HD) 1080p video sequences. This work is an extension to our previous comparative study published in previous SPIE conferences [1, 2]. Here we further optimize all three codecs for compression performance. Coding simulations are performed on a set of large-format color images captured from mainstream digital cameras and 1080p HD video sequences commonly used for H.264/AVC standardization work. Overall, our experimental results show that all three codecs offer very similar coding performances at the high-quality, high-resolution setting. Differences tend to be data-dependent: JPEG2000 with the wavelet technology tends to be the best performer with smooth spatial data; H.264/AVC High-Profile with advanced spatial prediction modes tends to cope best with more complex visual content; Microsoft HD Photo tends to be the most consistent across the board. For the still-image data sets, JPEG2000 offers the best R-D performance gains (around 0.2 to 1 dB in peak signal-to-noise ratio) over H.264/AVC High-Profile intra coding and Microsoft HD Photo. For the 1080p video data set, all three codecs offer very similar coding performance. As in [1, 2], neither do we consider scalability nor complexity in this study (JPEG2000 is operating in non-scalable, but optimal performance mode).

  20. A symbolic shaped-based retrieval of skull images.

    PubMed

    Lin, H Jill; Ruiz-Correa, Salvador; Shapiro, Linda G; Cunningham, Michael L; Sze, Raymond W

    2005-01-01

    In this work, we describe a novel symbolic representation of shapes for quantifying skull abnormalities in children with craniosynostosis. We show the efficacy of our work by demonstrating an application of this representation in shape-based retrieval of skull morphologies. This tool will enable correlation with potential pathogenesis and prognosis in order to enhance medical care.

  1. Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

    NASA Astrophysics Data System (ADS)

    Miao, X.; Xie, H.; Li, Z.; Lei, R.

    2013-12-01

    The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture

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

    PubMed

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

    2004-10-01

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

  3. Minimizing the semantic gap in biomedical content-based image retrieval

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

  4. Content-based cell pathology image retrieval by combining different features

    NASA Astrophysics Data System (ADS)

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

    2004-04-01

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

  5. Video and image retrieval beyond the cognitive level: the needs and possibilities

    NASA Astrophysics Data System (ADS)

    Hanjalic, Alan

    2000-12-01

    The worldwide research efforts in the are of image and video retrieval have concentrated so far on increasing the efficiency and reliability of extracting the elements of image and video semantics and so on improving the search and retrieval performance at the cognitive level of content abstraction. At this abstraction level, the user is searching for 'factual' or 'objective' content such as image showing a panorama of San Francisco, an outdoor or an indoor image, a broadcast news report on a defined topic, a movie dialog between the actors A and B or the parts of a basketball game showing fast breaks, steals and scores. These efforts, however, do not address the retrieval applications at the so-called affective level of content abstraction where the 'ground truth' is not strictly defined. Such applications are, for instance, those where subjectivity of the user plays the major role, e.g. the task of retrieving all images that the user 'likes most', and those that are based on 'recognizing emotions' in audiovisual data. Typical examples are searching for all images that 'radiate happiness', identifying all 'sad' movie fragments and looking for the 'romantic landscapes', 'sentimental' movie segments, 'movie highlights' or 'most exciting' moments of a sport event. This paper discusses the needs and possibilities for widening the current scope of research in the area of image and video search and retrieval in order to enable applications at the affective level of content abstraction.

  6. Video and image retrieval beyond the cognitive level: the needs and possibilities

    NASA Astrophysics Data System (ADS)

    Hanjalic, Alan

    2001-01-01

    The worldwide research efforts in the are of image and video retrieval have concentrated so far on increasing the efficiency and reliability of extracting the elements of image and video semantics and so on improving the search and retrieval performance at the cognitive level of content abstraction. At this abstraction level, the user is searching for 'factual' or 'objective' content such as image showing a panorama of San Francisco, an outdoor or an indoor image, a broadcast news report on a defined topic, a movie dialog between the actors A and B or the parts of a basketball game showing fast breaks, steals and scores. These efforts, however, do not address the retrieval applications at the so-called affective level of content abstraction where the 'ground truth' is not strictly defined. Such applications are, for instance, those where subjectivity of the user plays the major role, e.g. the task of retrieving all images that the user 'likes most', and those that are based on 'recognizing emotions' in audiovisual data. Typical examples are searching for all images that 'radiate happiness', identifying all 'sad' movie fragments and looking for the 'romantic landscapes', 'sentimental' movie segments, 'movie highlights' or 'most exciting' moments of a sport event. This paper discusses the needs and possibilities for widening the current scope of research in the area of image and video search and retrieval in order to enable applications at the affective level of content abstraction.

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

    PubMed

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

    2015-08-01

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

  8. A graph-based approach for the retrieval of multi-modality medical images.

    PubMed

    Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

    2014-02-01

    In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state

  9. High Resolution Imaging Using Phase Retrieval. Volume 2

    DTIC Science & Technology

    1991-10-01

    aberrations of the telescope. It will also correct aberrations due to atmospheric turbulence for a ground- based telescope, and can be used with several other...retrieval algorithm, based on the Ayers/Dainty blind deconvolution algorithm, was also developed. A new methodology for exploring the uniqueness of phase...Simulation Experiments ..................... 42 3.3.1 Initial Simulations with Noisy Modulus Data ..... 45 3.3.2 Simulations of a Space- Based Amplitude

  10. Landmark Image Retrieval by Jointing Feature Refinement and Multimodal Classifier Learning.

    PubMed

    Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun; Ma, Shuai; Xiaoming Zhang; Senzhang Wang; Zhoujun Li; Shuai Ma; Ma, Shuai; Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun

    2018-06-01

    Landmark retrieval is to return a set of images with their landmarks similar to those of the query images. Existing studies on landmark retrieval focus on exploiting the geometries of landmarks for visual similarity matches. However, the visual content of social images is of large diversity in many landmarks, and also some images share common patterns over different landmarks. On the other side, it has been observed that social images usually contain multimodal contents, i.e., visual content and text tags, and each landmark has the unique characteristic of both visual content and text content. Therefore, the approaches based on similarity matching may not be effective in this environment. In this paper, we investigate whether the geographical correlation among the visual content and the text content could be exploited for landmark retrieval. In particular, we propose an effective multimodal landmark classification paradigm to leverage the multimodal contents of social image for landmark retrieval, which integrates feature refinement and landmark classifier with multimodal contents by a joint model. The geo-tagged images are automatically labeled for classifier learning. Visual features are refined based on low rank matrix recovery, and multimodal classification combined with group sparse is learned from the automatically labeled images. Finally, candidate images are ranked by combining classification result and semantic consistence measuring between the visual content and text content. Experiments on real-world datasets demonstrate the superiority of the proposed approach as compared to existing methods.

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

    PubMed

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

    2018-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  13. Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

    NASA Astrophysics Data System (ADS)

    Xiang, Zhongbo; Li, Yanqiu

    2017-10-01

    Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

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

    PubMed

    Radley, Alan; Taylor, Diane

    2003-01-01

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

  15. Earth observation photo taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Earth observation photo taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). Image of California's coast from Point Concepcion (far left) to Ventura (right). The city of Santa Barbara is visible as a bright region (center). The row of bright spots in the ocean are oil drilling platforms in the Santa Barbara Channel, while the random points of brightness in the channel are vessels. Lakes Cachuma (left) and Casitas (right) are seen as large dark areas. Folded sedimentary rock layers are visible in the Santa Ynez Mountain Range which stretches down the coastline; the stratification terminates at the Santa Ynez fault on the island side of the mountains.

  16. Chinese Herbal Medicine Image Recognition and Retrieval by Convolutional Neural Network

    PubMed Central

    Sun, Xin; Qian, Huinan

    2016-01-01

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

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

    PubMed

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

    2015-10-01

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

  18. Content Based Image Retrieval and Information Theory: A General Approach.

    ERIC Educational Resources Information Center

    Zachary, John; Iyengar, S. S.; Barhen, Jacob

    2001-01-01

    Proposes an alternative real valued representation of color based on the information theoretic concept of entropy. A theoretical presentation of image entropy is accompanied by a practical description of the merits and limitations of image entropy compared to color histograms. Results suggest that image entropy is a promising approach to image…

  19. 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.

  20. Improving Concept-Based Web Image Retrieval by Mixing Semantically Similar Greek Queries

    ERIC Educational Resources Information Center

    Lazarinis, Fotis

    2008-01-01

    Purpose: Image searching is a common activity for web users. Search engines offer image retrieval services based on textual queries. Previous studies have shown that web searching is more demanding when the search is not in English and does not use a Latin-based language. The aim of this paper is to explore the behaviour of the major search…

  1. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image , Enid Photo Date: June 5, 1966 Photographer: Leo Ainsworth Credit: NOAA Photo Library, NOAA Central

  2. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Oklahoma, Altus Photo Date: May 20, 1977 Photographer: D. Burgess Credit: NOAA Photo Library

  3. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Oklahoma, Arcadia Photo Date: June 8, 1974 Photographer: D. Burgess Credit: NOAA Photo Library

  4. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: SW of Cheyenne, Oklahoma Photo Date: May 16, 1977 Credit: NOAA Photo Library, NOAA Central

  5. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image ) Collection Location: Texas, Wichita Falls Photo Date: April 10, 1979 Credit: NOAA Photo Library, NOAA Central

  6. 77 FR 21994 - Certain Digital Photo Frames and Image Display Devices and Components Thereof; Notice of Request...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-12

    ... Image Display Devices and Components Thereof; Notice of Request for Written Submissions on Remedy, the... importation, and the sale within the United States after importation of certain digital photo frames and image... the President, has 60 days to approve or disapprove the Commission's action. See section 337(j), 19 U...

  7. 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.

  8. 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.

  9. Similarity estimation for reference image retrieval in mammograms using convolutional neural network

    NASA Astrophysics Data System (ADS)

    Muramatsu, Chisako; Higuchi, Shunichi; Morita, Takako; Oiwa, Mikinao; Fujita, Hiroshi

    2018-02-01

    Periodic breast cancer screening with mammography is considered effective in decreasing breast cancer mortality. For screening programs to be successful, an intelligent image analytic system may support radiologists' efficient image interpretation. In our previous studies, we have investigated image retrieval schemes for diagnostic references of breast lesions on mammograms and ultrasound images. Using a machine learning method, reliable similarity measures that agree with radiologists' similarity were determined and relevant images could be retrieved. However, our previous method includes a feature extraction step, in which hand crafted features were determined based on manual outlines of the masses. Obtaining the manual outlines of masses is not practical in clinical practice and such data would be operator-dependent. In this study, we investigated a similarity estimation scheme using a convolutional neural network (CNN) to skip such procedure and to determine data-driven similarity scores. By using CNN as feature extractor, in which extracted features were employed in determination of similarity measures with a conventional 3-layered neural network, the determined similarity measures were correlated well with the subjective ratings and the precision of retrieving diagnostically relevant images was comparable with that of the conventional method using handcrafted features. By using CNN for determination of similarity measure directly, the result was also comparable. By optimizing the network parameters, results may be further improved. The proposed method has a potential usefulness in determination of similarity measure without precise lesion outlines for retrieval of similar mass images on mammograms.

  10. Three-dimensional imaging using phase retrieval with two focus planes

    NASA Astrophysics Data System (ADS)

    Ilovitsh, Tali; Ilovitsh, Asaf; Weiss, Aryeh; Meir, Rinat; Zalevsky, Zeev

    2016-03-01

    This work presents a technique for a full 3D imaging of biological samples tagged with gold-nanoparticles (GNPs) using only two images, rather than many images per volume as is currently needed for 3D optical sectioning microscopy. The proposed approach is based on the Gerchberg-Saxton (GS) phase retrieval algorithm. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. In addition, since the method requires the capturing of two images only, it can be suitable for 3D live cell imaging. The proposed concept is presented and validated both on simulated data as well as experimentally.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

    Okumura, Hiroshi; Yamasaki, Ryohei; Arai, Kohei

    2008-10-01

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

  13. Multi-instance learning based on instance consistency for image retrieval

    NASA Astrophysics Data System (ADS)

    Zhang, Miao; Wu, Zhize; Wan, Shouhong; Yue, Lihua; Yin, Bangjie

    2017-07-01

    Multiple-instance learning (MIL) has been successfully utilized in image retrieval. Existing approaches cannot select positive instances correctly from positive bags which may result in a low accuracy. In this paper, we propose a new image retrieval approach called multiple instance learning based on instance-consistency (MILIC) to mitigate such issue. First, we select potential positive instances effectively in each positive bag by ranking instance-consistency (IC) values of instances. Then, we design a feature representation scheme, which can represent the relationship among bags and instances, based on potential positive instances to convert a bag into a single instance. Finally, we can use a standard single-instance learning strategy, such as the support vector machine, for performing object-based image retrieval. Experimental results on two challenging data sets show the effectiveness of our proposal in terms of accuracy and run time.

  14. Retrieval of cloud cover parameters from multispectral satellite images

    NASA Technical Reports Server (NTRS)

    Arking, A.; Childs, J. D.

    1985-01-01

    A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

  15. Model-based magnetization retrieval from holographic phase images.

    PubMed

    Röder, Falk; Vogel, Karin; Wolf, Daniel; Hellwig, Olav; Wee, Sung Hun; Wicht, Sebastian; Rellinghaus, Bernd

    2017-05-01

    The phase shift of the electron wave is a useful measure for the projected magnetic flux density of magnetic objects at the nanometer scale. More important for materials science, however, is the knowledge about the magnetization in a magnetic nano-structure. As demonstrated here, a dominating presence of stray fields prohibits a direct interpretation of the phase in terms of magnetization modulus and direction. We therefore present a model-based approach for retrieving the magnetization by considering the projected shape of the nano-structure and assuming a homogeneous magnetization therein. We apply this method to FePt nano-islands epitaxially grown on a SrTiO 3 substrate, which indicates an inclination of their magnetization direction relative to the structural easy magnetic [001] axis. By means of this real-world example, we discuss prospects and limits of this approach. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. An image retrieval framework for real-time endoscopic image retargeting.

    PubMed

    Ye, Menglong; Johns, Edward; Walter, Benjamin; Meining, Alexander; Yang, Guang-Zhong

    2017-08-01

    Serial endoscopic examinations of a patient are important for early diagnosis of malignancies in the gastrointestinal tract. However, retargeting for optical biopsy is challenging due to extensive tissue variations between examinations, requiring the method to be tolerant to these changes whilst enabling real-time retargeting. This work presents an image retrieval framework for inter-examination retargeting. We propose both a novel image descriptor tolerant of long-term tissue changes and a novel descriptor matching method in real time. The descriptor is based on histograms generated from regional intensity comparisons over multiple scales, offering stability over long-term appearance changes at the higher levels, whilst remaining discriminative at the lower levels. The matching method then learns a hashing function using random forests, to compress the string and allow for fast image comparison by a simple Hamming distance metric. A dataset that contains 13 in vivo gastrointestinal videos was collected from six patients, representing serial examinations of each patient, which includes videos captured with significant time intervals. Precision-recall for retargeting shows that our new descriptor outperforms a number of alternative descriptors, whilst our hashing method outperforms a number of alternative hashing approaches. We have proposed a novel framework for optical biopsy in serial endoscopic examinations. A new descriptor, combined with a novel hashing method, achieves state-of-the-art retargeting, with validation on in vivo videos from six patients. Real-time performance also allows for practical integration without disturbing the existing clinical workflow.

  17. 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.

  18. Surface Chemistry Manipulation of Gold Nanorods Displays High Cellular Uptake In Vitro While Preserving Optical Properties for Bio-Imaging and Photo-Thermal Applications

    DTIC Science & Technology

    2016-03-28

    PROPERTIES FOR BIO -IMAGING AND PHOTO-THERMAL APPLICATIONS ANTHONY B. POLITO III, Maj, USAF, BSC, PhD, MT(ASCP)SBB March 2016 Final Report for March...HIGH CELLULAR UPTAKE IN VITRO WHILE PRESERVING OPTICAL PROPERTIES FOR BIO -IMAGING AND PHOTO-THERMAL APPLICATIONS. 5a. CONTRACT NUMBER 5b...These findings identify MTAB-TA GNRs as prime candidates for use in nano-based bio -imaging and photo-thermal applications. 15. SUBJECT TERMS

  19. Content-based retrieval of historical Ottoman documents stored as textual images.

    PubMed

    Saykol, Ediz; Sinop, Ali Kemal; Güdükbay, Ugur; Ulusoy, Ozgür; Cetin, A Enis

    2004-03-01

    There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts.

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

    NASA Astrophysics Data System (ADS)

    Wei, Yuchun

    2008-04-01

    Thin fog, which often appears in remote sensing image of subtropical climate region, has resulted in the low image quantity and bad image mapping. Therefore, it is necessary to develop the image processing method to retrieve land cover information under thin fog. In this paper, the Landsat TM image near the Taihu Lake that is in the subtropical climate zone of China was used as an example, and the workflow and method used to retrieve the land cover information under thin fog have been built based on ENVI software and a single TM image. The basic step covers three parts: 1) isolating the thin fog area in image according to the spectral difference of different bands; 2) retrieving the visible band information of different land cover types under thin fog from the near-infrared bands according to the relationships between near-infrared bands and visible bands of different land cover types in the area without fog; 3) image post-process. The result showed that the method in the paper is easy and suitable, and can be used to improve the quantity of TM image mapping more effectively.

  1. Content-based image retrieval by matching hierarchical attributed region adjacency graphs

    NASA Astrophysics Data System (ADS)

    Fischer, Benedikt; Thies, Christian J.; Guld, Mark O.; Lehmann, Thomas M.

    2004-05-01

    Content-based image retrieval requires a formal description of visual information. In medical applications, all relevant biological objects have to be represented by this description. Although color as the primary feature has proven successful in publicly available retrieval systems of general purpose, this description is not applicable to most medical images. Additionally, it has been shown that global features characterizing the whole image do not lead to acceptable results in the medical context or that they are only suitable for specific applications. For a general purpose content-based comparison of medical images, local, i.e. regional features that are collected on multiple scales must be used. A hierarchical attributed region adjacency graph (HARAG) provides such a representation and transfers image comparison to graph matching. However, building a HARAG from an image requires a restriction in size to be computationally feasible while at the same time all visually plausible information must be preserved. For this purpose, mechanisms for the reduction of the graph size are presented. Even with a reduced graph, the problem of graph matching remains NP-complete. In this paper, the Similarity Flooding approach and Hopfield-style neural networks are adapted from the graph matching community to the needs of HARAG comparison. Based on synthetic image material build from simple geometric objects, all visually similar regions were matched accordingly showing the framework's general applicability to content-based image retrieval of medical images.

  2. Inter-Comparison of GOES-8 Imager and Sounder Skin Temperature Retrievals

    NASA Technical Reports Server (NTRS)

    Haines, Stephanie L.; Suggs, Ronnie J.; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)

    2001-01-01

    Skin temperature (ST) retrievals derived from geostationary satellite observations have both high temporal and spatial resolutions and are therefore useful for applications such as assimilation into mesoscale forecast models, nowcasting, and diagnostic studies. Our retrieval method uses a Physical Split Window technique requiring at least two channels within the longwave infrared window. On current GOES satellites, including GOES-11, there are two Imager channels within the required spectral interval. However, beginning with the GOES-M satellite the 12-um channel will be removed, leaving only one longwave channel. The Sounder instrument will continue to have three channels within the longwave window, and therefore ST retrievals will be derived from Sounder measurements. This research compares retrievals from the two instruments and evaluates the effects of the spatial resolution and sensor calibration differences on the retrievals. Both Imager and Sounder retrievals are compared to ground-truth data to evaluate the overall accuracy of the technique. An analysis of GOES-8 and GOES-11 intercomparisons is also presented.

  3. Hierarchical content-based image retrieval by dynamic indexing and guided search

    NASA Astrophysics Data System (ADS)

    You, Jane; Cheung, King H.; Liu, James; Guo, Linong

    2003-12-01

    This paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. The proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone pattern recognition, and personal identification using multi-level palmprint and face features.

  4. Photos of earth observations taken by JPL with the Shuttle Imaging Radar-A

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Photos of earth observations taken by the Jet Propulsion Laboratory (JPL) with the Shuttle Imaging Radar-A (SIR-A). The first image show northern Peloponnesia and part of southern Greece. The Corinthian Canal is visible as a bright line cutting across the narrow Corinth Isthmus (upper center). Black area to the right is the Aegian Sea; on the left, the Gulf of Corinth. Islands to the right, starting at the top, are Salamis, Aegene and Angistrion, and the Peninsula of Methana. Southwest of the canal on the gulf coast is the city of Corinth, appearing as bright, white spots (40244); This image shows the Hamersley mountain range in Western Australia. A circular pattern of eroded folds surround a prominent granite dome, remnants of a volcanic past, is seen in the center of the photograph. The Hardey River is seen running vertically to the right of the center circular dome, and the small town of Paraburdoo appears as a patch of tiny bright rectangles in the lower right corner (40245).

  5. Facebook photo activity associated with body image disturbance in adolescent girls.

    PubMed

    Meier, Evelyn P; Gray, James

    2014-04-01

    The present study examined the relationship between body image and adolescent girls' activity on the social networking site (SNS) Facebook (FB). Research has shown that elevated Internet "appearance exposure" is positively correlated with increased body image disturbance among adolescent girls, and there is a particularly strong association with FB use. The present study sought to replicate and extend upon these findings by identifying the specific FB features that correlate with body image disturbance in adolescent girls. A total of 103 middle and high school females completed questionnaire measures of total FB use, specific FB feature use, weight dissatisfaction, drive for thinness, thin ideal internalization, appearance comparison, and self-objectification. An appearance exposure score was calculated based on subjects' use of FB photo applications relative to total FB use. Elevated appearance exposure, but not overall FB usage, was significantly correlated with weight dissatisfaction, drive for thinness, thin ideal internalization, and self-objectification. Implications for eating disorder prevention programs and best practices in researching SNSs are discussed.

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

    NASA Astrophysics Data System (ADS)

    QingJie, Wei; WenBin, Wang

    2017-06-01

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

  7. 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.

  8. Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

    NASA Astrophysics Data System (ADS)

    Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

    2018-06-01

    An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

  9. Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

    NASA Technical Reports Server (NTRS)

    Platnick, Steven

    2004-01-01

    MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

  10. Effectiveness of image features and similarity measures in cluster-based approaches for content-based image retrieval

    NASA Astrophysics Data System (ADS)

    Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin

    2014-05-01

    Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.

  11. Statistical Techniques for Efficient Indexing and Retrieval of Document Images

    ERIC Educational Resources Information Center

    Bhardwaj, Anurag

    2010-01-01

    We have developed statistical techniques to improve the performance of document image search systems where the intermediate step of OCR based transcription is not used. Previous research in this area has largely focused on challenges pertaining to generation of small lexicons for processing handwritten documents and enhancement of poor quality…

  12. Genetic Algorithm Phase Retrieval for the Systematic Image-Based Optical Alignment Testbed

    NASA Technical Reports Server (NTRS)

    Taylor, Jaime; Rakoczy, John; Steincamp, James

    2003-01-01

    Phase retrieval requires calculation of the real-valued phase of the pupil fimction from the image intensity distribution and characteristics of an optical system. Genetic 'algorithms were used to solve two one-dimensional phase retrieval problem. A GA successfully estimated the coefficients of a polynomial expansion of the phase when the number of coefficients was correctly specified. A GA also successfully estimated the multiple p h e s of a segmented optical system analogous to the seven-mirror Systematic Image-Based Optical Alignment (SIBOA) testbed located at NASA s Marshall Space Flight Center. The SIBOA testbed was developed to investigate phase retrieval techniques. Tiphilt and piston motions of the mirrors accomplish phase corrections. A constant phase over each mirror can be achieved by an independent tip/tilt correction: the phase Conection term can then be factored out of the Discrete Fourier Tranform (DFT), greatly reducing computations.

  13. Wavelet optimization for content-based image retrieval in medical databases.

    PubMed

    Quellec, G; Lamard, M; Cazuguel, G; Cochener, B; Roux, C

    2010-04-01

    We propose in this article a content-based image retrieval (CBIR) method for diagnosis aid in medical fields. In the proposed system, images are indexed in a generic fashion, without extracting domain-specific features: a signature is built for each image from its wavelet transform. These image signatures characterize the distribution of wavelet coefficients in each subband of the decomposition. A distance measure is then defined to compare two image signatures and thus retrieve the most similar images in a database when a query image is submitted by a physician. To retrieve relevant images from a medical database, the signatures and the distance measure must be related to the medical interpretation of images. As a consequence, we introduce several degrees of freedom in the system so that it can be tuned to any pathology and image modality. In particular, we propose to adapt the wavelet basis, within the lifting scheme framework, and to use a custom decomposition scheme. Weights are also introduced between subbands. All these parameters are tuned by an optimization procedure, using the medical grading of each image in the database to define a performance measure. The system is assessed on two medical image databases: one for diabetic retinopathy follow up and one for screening mammography, as well as a general purpose database. Results are promising: a mean precision of 56.50%, 70.91% and 96.10% is achieved for these three databases, when five images are returned by the system. Copyright 2009 Elsevier B.V. All rights reserved.

  14. Images

    Science.gov Websites

    : Upload Date Photo Date 1 2 3 4 5 Next Arctic Edge 2018 Download Full Image Photo Details Arctic Edge 2018 Download Full Image Photo Details Arctic Edge 2018 Download Full Image Photo Details Arctic Edge 2018 Download Full Image Photo Details Arctic Edge 2018 Download Full Image Photo Details Arctic Edge 2018

  15. A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

    PubMed Central

    Rahman, M. M.; Antani, S. K.; Thoma, G. R.

    2011-01-01

    We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

  16. 4D reconstruction of the past: the image retrieval and 3D model construction pipeline

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  17. Qualification of a Null Lens Using Image-Based Phase Retrieval

    NASA Technical Reports Server (NTRS)

    Bolcar, Matthew R.; Aronstein, David L.; Hill, Peter C.; Smith, J. Scott; Zielinski, Thomas P.

    2012-01-01

    In measuring the figure error of an aspheric optic using a null lens, the wavefront contribution from the null lens must be independently and accurately characterized in order to isolate the optical performance of the aspheric optic alone. Various techniques can be used to characterize such a null lens, including interferometry, profilometry and image-based methods. Only image-based methods, such as phase retrieval, can measure the null-lens wavefront in situ - in single-pass, and at the same conjugates and in the same alignment state in which the null lens will ultimately be used - with no additional optical components. Due to the intended purpose of a Dull lens (e.g., to null a large aspheric wavefront with a near-equal-but-opposite spherical wavefront), characterizing a null-lens wavefront presents several challenges to image-based phase retrieval: Large wavefront slopes and high-dynamic-range data decrease the capture range of phase-retrieval algorithms, increase the requirements on the fidelity of the forward model of the optical system, and make it difficult to extract diagnostic information (e.g., the system F/#) from the image data. In this paper, we present a study of these effects on phase-retrieval algorithms in the context of a null lens used in component development for the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission. Approaches for mitigation are also discussed.

  18. Algorithm design for automated transportation photo enforcement camera image and video quality diagnostic check modules

    NASA Astrophysics Data System (ADS)

    Raghavan, Ajay; Saha, Bhaskar

    2013-03-01

    Photo enforcement devices for traffic rules such as red lights, toll, stops, and speed limits are increasingly being deployed in cities and counties around the world to ensure smooth traffic flow and public safety. These are typically unattended fielded systems, and so it is important to periodically check them for potential image/video quality problems that might interfere with their intended functionality. There is interest in automating such checks to reduce the operational overhead and human error involved in manually checking large camera device fleets. Examples of problems affecting such camera devices include exposure issues, focus drifts, obstructions, misalignment, download errors, and motion blur. Furthermore, in some cases, in addition to the sub-algorithms for individual problems, one also has to carefully design the overall algorithm and logic to check for and accurately classifying these individual problems. Some of these issues can occur in tandem or have the potential to be confused for each other by automated algorithms. Examples include camera misalignment that can cause some scene elements to go out of focus for wide-area scenes or download errors that can be misinterpreted as an obstruction. Therefore, the sequence in which the sub-algorithms are utilized is also important. This paper presents an overview of these problems along with no-reference and reduced reference image and video quality solutions to detect and classify such faults.

  19. Simulating Photo-Refraction Images of Keratoconus and Near-Sightedness Eyes

    NASA Astrophysics Data System (ADS)

    Baker, Kevin; Lewis, James W. L.; Chen, Ying-Ling

    2004-11-01

    Keratoconus is an abnormal condition of the eye resulting from cone-shaped features on the cornea that degrade the quality of vision. These corneal features result from thinning and subsequent bulging due to intraocular pressure. The abnormal corneal curvature increases the refractive power asymmetrically and can be misdiagnosed by examiners as astigmatism and nearsightedness. Since corrective treatment is possible, early detection of this condition is desirable. Photo-refraction (PR) detects the retinal irradiance reflected from a single light source and is an inexpensive method used to identify refractive errors. For near- (far-) sighted eye, a crescent appears on the same (opposite) side of the light source. The capability of a PR device to detect keratoconus and to differentiate this condition from myopia was investigated. Using a commercial optical program, synthetic eye models were constructed for both near-sighted and keratoconus eyes. PR images of various eye conditions were calculated. The keratoconus cone shapes were modeled with typical published cone locations and sizes. The results indicate significant differences between the images of keratoconus and near-sighted eyes.

  20. Retrievals of aerosol optical and microphysical properties from Imaging Polar Nephelometer scattering measurements

    NASA Astrophysics Data System (ADS)

    Reed Espinosa, W.; Remer, Lorraine A.; Dubovik, Oleg; Ziemba, Luke; Beyersdorf, Andreas; Orozco, Daniel; Schuster, Gregory; Lapyonok, Tatyana; Fuertes, David; Vanderlei Martins, J.

    2017-03-01

    A method for the retrieval of aerosol optical and microphysical properties from in situ light-scattering measurements is presented and the results are compared with existing measurement techniques. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to airborne and laboratory measurements made by a novel polar nephelometer. This instrument, the Polarized Imaging Nephelometer (PI-Neph), is capable of making high-accuracy field measurements of phase function and degree of linear polarization, at three visible wavelengths, over a wide angular range of 3 to 177°. The resulting retrieval produces particle size distributions (PSDs) that agree, within experimental error, with measurements made by commercial optical particle counters (OPCs). Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, with a refractive index that is well established. The airborne measurements used in this work were made aboard the NASA DC-8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field campaign, and the inversion of this data represents the first aerosol retrievals of airborne polar nephelometer data. The results provide confidence in the real refractive index product, as well as in the retrieval's ability to accurately determine PSD, without assumptions about refractive index that are required by the majority of OPCs.

  1. PhotoExam: adoption of an iOS-based clinical image capture application at Mayo Clinic.

    PubMed

    Wyatt, Kirk D; Willaert, Brian N; Pallagi, Peter J; Uribe, Richard A; Yiannias, James A; Hellmich, Thomas R

    2017-12-01

    Mayo Clinic developed an internal iOS-based, point-of-care clinical image capture application for clinicians. We aimed to assess the adoption and utilization of the application at Mayo Clinic. Metadata of 22,784 photos of 6417 patients taken by 606 users over 8040 clinical encounters between 3/1/2015 and 10/31/2015 were analyzed. A random sample of photos from 100 clinical encounters was assessed for quality using a five-item rubric. Use of traditional medical photography services before and after application launch were compared. The largest group of users was residents/fellows, accounting for 31% of users but only 18% of all photos. Attending physicians accounted for 29% of users and 30% of photos. Nurses accounted for 14% of users and 28% of photos. Surgical specialties had the most users (36% of users), followed by dermatology (14% of users); however, dermatology accounted for 54% of all photos, and surgery accounted for 26% of photos. Images received an average of 91% of possible points on the quality scoring rubric. Most frequent reasons for missing points were the location on the body not clearly being demonstrated (19% of encounters) and the perspective/scale not being clearly demonstrated (12% of encounters). There was no discernible pre-post effect of the application's launch on use of traditional medical photography services. Point-of-care clinical photography is a growing phenomenon with potential to become the new standard of care. Patient and provider attitudes and the impact on patient outcomes remain unclear. © 2017 The International Society of Dermatology.

  2. Large Scale Hierarchical K-Means Based Image Retrieval With MapReduce

    DTIC Science & Technology

    2014-03-27

    hadoop distributed file system: Architecture and design, 2007. [10] G. Bradski. Dr. Dobb’s Journal of Software Tools, 2000. [11] Terry Costlow. Big data ...million images running on 20 virtual machines are shown. 15. SUBJECT TERMS Image Retrieval, MapReduce, Hierarchical K-Means, Big Data , Hadoop U U U UU 87...13 2.1.1.2 HDFS Data Representation . . . . . . . . . . . . . . . . 14 2.1.1.3 Hadoop Engine

  3. Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

    NASA Technical Reports Server (NTRS)

    Chang, L. Aron

    1995-01-01

    This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

  4. Surface reflectance retrieval from imaging spectrometer data using three atmospheric codes

    NASA Astrophysics Data System (ADS)

    Staenz, Karl; Williams, Daniel J.; Fedosejevs, Gunar; Teillet, Phil M.

    1994-12-01

    Surface reflectance retrieval from imaging spectrometer data has become important for quantitative information extraction in many application areas. In order to calculate surface reflectance from remotely measured radiance, radiative transfer codes play an important role for removal of the scattering and gaseous absorption effects of the atmosphere. The present study evaluates surface reflectances retrieved from airborne visible/infrared imaging spectrometer (AVIRIS) data using three radiative transfer codes: modified 5S (M5S), 6S, and MODTRAN2. Comparisons of the retrieved surface reflectance with ground-based reflectance were made for different target types such as asphalt, gravel, grass/soil mixture (soccer field), and water (Sooke Lake). The results indicate that the estimation of the atmospheric water vapor content is important for an accurate surface reflectance retrieval regardless of the radiative transfer code used. For the present atmospheric conditions, a difference of 0.1 in aerosol optical depth had little impact on the retrieved surface reflectance. The performance of MODTRAN2 is superior in the gas absorption regions compared to M5S and 6S.

  5. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

    NASA Astrophysics Data System (ADS)

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2016-04-01

    This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

  6. Color image encryption using random transforms, phase retrieval, chaotic maps, and diffusion

    NASA Astrophysics Data System (ADS)

    Annaby, M. H.; Rushdi, M. A.; Nehary, E. A.

    2018-04-01

    The recent tremendous proliferation of color imaging applications has been accompanied by growing research in data encryption to secure color images against adversary attacks. While recent color image encryption techniques perform reasonably well, they still exhibit vulnerabilities and deficiencies in terms of statistical security measures due to image data redundancy and inherent weaknesses. This paper proposes two encryption algorithms that largely treat these deficiencies and boost the security strength through novel integration of the random fractional Fourier transforms, phase retrieval algorithms, as well as chaotic scrambling and diffusion. We show through detailed experiments and statistical analysis that the proposed enhancements significantly improve security measures and immunity to attacks.

  7. Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

    NASA Astrophysics Data System (ADS)

    Aggarwal, Preeti; Sardana, H. K.

    2010-02-01

    Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

  8. Retrieval of the thickness of undeformed sea ice from C-band compact polarimetric SAR images

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Dierking, W.; Zhang, J.; Meng, J. M.; Lang, H. T.

    2015-10-01

    In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. The parameter is denoted as "CP-Ratio". In model simulations we investigated the sensitivity of CP-Ratio to the dielectric constant, thickness, surface roughness, and incidence angle. From the results of the simulations we deduced optimal conditions for the thickness retrieval. On the basis of C-band CTLR SAR data, which were generated from Radarsat-2 quad-polarization images acquired jointly with helicopter-borne sea ice thickness measurements in the region of the Sea of Labrador, we tested empirical equations for thickness retrieval. An exponential fit between CP-Ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.92 for the retrieval procedure when applying it on level ice of 0.9 m mean thickness.

  9. Phase retrieval on broadband and under-sampled images for the JWST testbed telescope

    NASA Astrophysics Data System (ADS)

    Smith, J. Scott; Aronstein, David L.; Dean, Bruce H.; Acton, D. Scott

    2009-08-01

    The James Webb Space Telescope (JWST) consists of an optical telescope element (OTE) that sends light to five science instruments. The initial steps for commissioning the telescope are performed with the Near-Infrared Camera (NIRCam) instrument, but low-order optical aberrations in the remaining science instruments must be determined (using phase retrieval) in order to ensure good performance across the entire field of view. These remaining instruments were designed to collect science data, and not to serve as wavefront sensors. Thus, the science cameras are not ideal phase-retrieval imagers for several reasons: they record under-sampled data and have a limited range of diversity defocus, and only one instrument has an internal, narrowband filter. To address these issues, we developed the capability of sensing these aberrations using an extension of image-based iterative-transform phase retrieval called Variable Sampling Mapping (VSM). The results show that VSM-based phase retrieval is capable of sensing low-order aberrations to a few nm RMS from images that are consistent with the non-ideal conditions expected during JWST multi-field commissioning. The algorithm is validated using data collected from the JWST Testbed Telescope (TBT).

  10. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

    PubMed

    Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

    2018-09-01

    Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

  11. 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.

  12. 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

  13. 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.

  14. Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

    PubMed

    Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

    2015-05-15

    We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

    PubMed

    Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

    2015-09-01

    With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

  16. Keywords image retrieval in historical handwritten Arabic documents

    NASA Astrophysics Data System (ADS)

    Saabni, Raid; El-Sana, Jihad

    2013-01-01

    A system is presented for spotting and searching keywords in handwritten Arabic documents. A slightly modified dynamic time warping algorithm is used to measure similarities between words. Two sets of features are generated from the outer contour of the words/word-parts. The first set is based on the angles between nodes on the contour and the second set is based on the shape context features taken from the outer contour. To recognize a given word, the segmentation-free approach is partially adopted, i.e., continuous word parts are used as the basic alphabet, instead of individual characters or complete words. Additional strokes, such as dots and detached short segments, are classified and used in a postprocessing step to determine the final comparison decision. The search for a keyword is performed by the search for its word parts given in the correct order. The performance of the presented system was very encouraging in terms of efficiency and match rates. To evaluate the presented system its performance is compared to three different systems. Unfortunately, there are no publicly available standard datasets with ground truth for testing Arabic key word searching systems. Therefore, a private set of images partially taken from Juma'a Al-Majid Center in Dubai for evaluation is used, while using a slightly modified version of the IFN/ENIT database for training.

  17. Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval.

    PubMed

    Zhang, Haofeng; Liu, Li; Long, Yang; Shao, Ling

    2018-04-01

    In order to achieve efficient similarity searching, hash functions are designed to encode images into low-dimensional binary codes with the constraint that similar features will have a short distance in the projected Hamming space. Recently, deep learning-based methods have become more popular, and outperform traditional non-deep methods. However, without label information, most state-of-the-art unsupervised deep hashing (DH) algorithms suffer from severe performance degradation for unsupervised scenarios. One of the main reasons is that the ad-hoc encoding process cannot properly capture the visual feature distribution. In this paper, we propose a novel unsupervised framework that has two main contributions: 1) we convert the unsupervised DH model into supervised by discovering pseudo labels; 2) the framework unifies likelihood maximization, mutual information maximization, and quantization error minimization so that the pseudo labels can maximumly preserve the distribution of visual features. Extensive experiments on three popular data sets demonstrate the advantages of the proposed method, which leads to significant performance improvement over the state-of-the-art unsupervised hashing algorithms.

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

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

  19. Assessment and application of AirMSPI high-resolution multiangle imaging photo-polarimetric observations for atmospheric correction

    NASA Astrophysics Data System (ADS)

    Kalashnikova, O. V.; Xu, F.; Garay, M. J.; Seidel, F. C.; Diner, D. J.

    2016-02-01

    Water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Modern improvements have been developed in ocean color retrieval algorithms to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean. In addition, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error in the retrieved water leaving radiance. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI typically acquires observations of a target area at 9 view angles between ±67° at 10 m resolution. AirMSPI spectral channels are centered at 355, 380, 445, 470, 555, 660, and 865 nm, with 470, 660, and 865 reporting linear polarization. We have developed a retrieval code that employs a coupled Markov Chain (MC) and adding/doubling radiative transfer method for joint retrieval of aerosol properties and water leaving radiance from AirMSPI polarimetric observations. We tested prototype retrievals by comparing the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentrations to values reported by the USC SeaPRISM AERONET-OC site off the coast of California. The retrieval then was applied to a variety of costal regions in California to evaluate variability in the water-leaving radiance under different atmospheric conditions. We will present results, and will discuss algorithm sensitivity and potential applications for future space-borne coastal monitoring.

  20. Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task.

    PubMed

    G Seco de Herrera, Alba; Schaer, Roger; Markonis, Dimitrios; Müller, Henning

    2015-01-01

    Retrieval systems can supply similar cases with a proven diagnosis to a new example case under observation to help clinicians during their work. The ImageCLEFmed evaluation campaign proposes a framework where research groups can compare case-based retrieval approaches. This paper focuses on the case-based task and adds results of the compound figure separation and modality classification tasks. Several fusion approaches are compared to identify the approaches best adapted to the heterogeneous data of the task. Fusion of visual and textual features is analyzed, demonstrating that the selection of the fusion strategy can improve the best performance on the case-based retrieval task. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Conjunctive patches subspace learning with side information for collaborative image retrieval.

    PubMed

    Zhang, Lining; Wang, Lipo; Lin, Weisi

    2012-08-01

    Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

  2. 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

  3. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

    PubMed

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2016-01-01

    This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

  4. Uncertainties in Cloud Phase and Optical Thickness Retrievals from the Earth Polychromatic Imaging Camera (EPIC)

    NASA Technical Reports Server (NTRS)

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2016-01-01

    This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (less than 2 percent) due to the particle- size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 percent, although for thin clouds (COT less than 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

  5. Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

    PubMed Central

    Meyer, Kerry; Yang, Yuekui; Platnick, Steven

    2018-01-01

    This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

  6. A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces

    NASA Astrophysics Data System (ADS)

    Wei, Jing; Huang, Bo; Sun, Lin; Zhang, Zhaoyang; Wang, Lunche; Bilal, Muhammad

    2017-12-01

    Operational aerosol optical depth (AOD) products are available at coarse spatial resolutions from several to tens of kilometers. These resolutions limit the application of these products for monitoring atmospheric pollutants at the city level. Therefore, a simple, universal, and high-resolution (30 m) Landsat aerosol retrieval algorithm over complex urban surfaces is developed. The surface reflectance is estimated from a combination of top of atmosphere reflectance at short-wave infrared (2.22 μm) and Landsat 4-7 surface reflectance climate data records over densely vegetated areas and bright areas. The aerosol type is determined using the historical aerosol optical properties derived from the local urban Aerosol Robotic Network (AERONET) site (Beijing). AERONET ground-based sun photometer AOD measurements from five sites located in urban and rural areas are obtained to validate the AOD retrievals. Terra MODerate resolution Imaging Spectrometer Collection (C) 6 AOD products (MOD04) including the dark target (DT), the deep blue (DB), and the combined DT and DB (DT&DB) retrievals at 10 km spatial resolution are obtained for comparison purposes. Validation results show that the Landsat AOD retrievals at a 30 m resolution are well correlated with the AERONET AOD measurements (R2 = 0.932) and that approximately 77.46% of the retrievals fall within the expected error with a low mean absolute error of 0.090 and a root-mean-square error of 0.126. Comparison results show that Landsat AOD retrievals are overall better and less biased than MOD04 AOD products, indicating that the new algorithm is robust and performs well in AOD retrieval over complex surfaces. The new algorithm can provide continuous and detailed spatial distributions of AOD during both low and high aerosol loadings.

  7. Imaging denatured collagen strands in vivo and ex vivo via photo-triggered hybridization of caged collagen mimetic peptides.

    PubMed

    Li, Yang; Foss, Catherine A; Pomper, Martin G; Yu, S Michael

    2014-01-31

    Collagen is a major structural component of the extracellular matrix that supports tissue formation and maintenance. Although collagen remodeling is an integral part of normal tissue renewal, excessive amount of remodeling activity is involved in tumors, arthritis, and many other pathological conditions. During collagen remodeling, the triple helical structure of collagen molecules is disrupted by proteases in the extracellular environment. In addition, collagens present in many histological tissue samples are partially denatured by the fixation and preservation processes. Therefore, these denatured collagen strands can serve as effective targets for biological imaging. We previously developed a caged collagen mimetic peptide (CMP) that can be photo-triggered to hybridize with denatured collagen strands by forming triple helical structure, which is unique to collagens. The overall goals of this procedure are i) to image denatured collagen strands resulting from normal remodeling activities in vivo, and ii) to visualize collagens in ex vivo tissue sections using the photo-triggered caged CMPs. To achieve effective hybridization and successful in vivo and ex vivo imaging, fluorescently labeled caged CMPs are either photo-activated immediately before intravenous injection, or are directly activated on tissue sections. Normal skeletal collagen remolding in nude mice and collagens in prefixed mouse cornea tissue sections are imaged in this procedure. The imaging method based on the CMP-collagen hybridization technology presented here could lead to deeper understanding of the tissue remodeling process, as well as allow development of new diagnostics for diseases associated with high collagen remodeling activity.

  8. Unsupervised symmetrical trademark image retrieval in soccer telecast using wavelet energy and quadtree decomposition

    NASA Astrophysics Data System (ADS)

    Ong, Swee Khai; Lim, Wee Keong; Soo, Wooi King

    2013-04-01

    Trademark, a distinctive symbol, is used to distinguish products or services provided by a particular person, group or organization from other similar entries. As trademark represents the reputation and credit standing of the owner, it is important to differentiate one trademark from another. Many methods have been proposed to identify, classify and retrieve trademarks. However, most methods required features database and sample sets for training prior to recognition and retrieval process. In this paper, a new feature on wavelet coefficients, the localized wavelet energy, is introduced to extract features of trademarks. With this, unsupervised content-based symmetrical trademark image retrieval is proposed without the database and prior training set. The feature analysis is done by an integration of the proposed localized wavelet energy and quadtree decomposed regional symmetrical vector. The proposed framework eradicates the dependence on query database and human participation during the retrieval process. In this paper, trademarks for soccer games sponsors are the intended trademark category. Video frames from soccer telecast are extracted and processed for this study. Reasonably good localization and retrieval results on certain categories of trademarks are achieved. A distinctive symbol is used to distinguish products or services provided by a particular person, group or organization from other similar entries.

  9. Hurricane Imaging Radiometer (HIRAD) Wind Speed Retrievals and Assessment Using Dropsondes

    NASA Technical Reports Server (NTRS)

    Cecil, Daniel J.; Biswas, Sayak K.

    2018-01-01

    The Hurricane Imaging Radiometer (HIRAD) is an experimental C-band passive microwave radiometer designed to map the horizontal structure of surface wind speed fields in hurricanes. New data processing and customized retrieval approaches were developed after the 2015 Tropical Cyclone Intensity (TCI) experiment, which featured flights over Hurricanes Patricia, Joaquin, Marty, and the remnants of Tropical Storm Erika. These new approaches produced maps of surface wind speed that looked more realistic than those from previous campaigns. Dropsondes from the High Definition Sounding System (HDSS) that was flown with HIRAD on a WB-57 high altitude aircraft in TCI were used to assess the quality of the HIRAD wind speed retrievals. The root mean square difference between HIRAD-retrieved surface wind speeds and dropsonde-estimated surface wind speeds was 6.0 meters per second. The largest differences between HIRAD and dropsonde winds were from data points where storm motion during dropsonde descent compromised the validity of the comparisons. Accounting for this and for uncertainty in the dropsonde measurements themselves, we estimate the root mean square error for the HIRAD retrievals as around 4.7 meters per second. Prior to the 2015 TCI experiment, HIRAD had previously flown on the WB-57 for missions across Hurricanes Gonzalo (2014), Earl (2010), and Karl (2010). Configuration of the instrument was not identical to the 2015 flights, but the methods devised after the 2015 flights may be applied to that previous data in an attempt to improve retrievals from those cases.

  10. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image - nssl0059 Tornado in mature stage of development. Photo #3 of a series of classic photographs of this

  11. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Storms Laboratory (NSSL) Collection Credit: NOAA Photo Library, NOAA Central Library; OAR/ERL/National

  12. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Photo Library, NOAA Central Library; OAR/ERL/National Severe Storms Laboratory (NSSL) Category

  13. Method for indexing and retrieving manufacturing-specific digital imagery based on image content

    DOEpatents

    Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

    2004-06-15

    A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

  14. Chickenpox (Varicella) Photos

    MedlinePlus

    ... advised. Click on any image to enlarge it. Images of People Affected by the Disease Chickenpox in ... vaccinated child. Courtesy of Varicella Active Surveillance Project Images of Varicella Zoster Virus PHIL Photo ID# 2791 ...

  15. Content-based image retrieval for interstitial lung diseases using classification confidence

    NASA Astrophysics Data System (ADS)

    Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

    2013-02-01

    Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

  16. Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

    NASA Technical Reports Server (NTRS)

    Sahawneh, Saleem; Farrar, Spencer; Johnson, James; Jones, W. Linwood; Roberts, Jason; Biswas, Sayak; Cecil, Daniel

    2014-01-01

    Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.

  17. Functional imaging of the semantic system: retrieval of sensory-experienced and verbally learned knowledge.

    PubMed

    Noppeney, Uta; Price, Cathy J

    2003-01-01

    This paper considers how functional neuro-imaging can be used to investigate the organization of the semantic system and the limitations associated with this technique. The majority of the functional imaging studies of the semantic system have looked for divisions by varying stimulus category. These studies have led to divergent results and no clear anatomical hypotheses have emerged to account for the dissociations seen in behavioral studies. Only a few functional imaging studies have used task as a variable to differentiate the neural correlates of semantic features more directly. We extend these findings by presenting a new study that contrasts tasks that differentially weight sensory (color and taste) and verbally learned (origin) semantic features. Irrespective of the type of semantic feature retrieved, a common semantic system was activated as demonstrated in many previous studies. In addition, the retrieval of verbally learned, but not sensory-experienced, features enhanced activation in medial and lateral posterior parietal areas. We attribute these "verbally learned" effects to differences in retrieval strategy and conclude that evidence for segregation of semantic features at an anatomical level remains weak. We believe that functional imaging has the potential to increase our understanding of the neuronal infrastructure that sustains semantic processing but progress may require multiple experiments until a consistent explanatory framework emerges.

  18. High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

    NASA Astrophysics Data System (ADS)

    Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

    2014-01-01

    The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

  19. Fusion of Deep Learning and Compressed Domain features for Content Based Image Retrieval.

    PubMed

    Liu, Peizhong; Guo, Jing-Ming; Wu, Chi-Yi; Cai, Danlin

    2017-08-29

    This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate. Two metrics, average precision rate (APR) and average recall rate (ARR), are employed to examine various datasets. As documented in the experimental results, the proposed schemes can achieve superior performance compared to the state-of-the-art methods with either low- or high-level features in terms of the retrieval rate. Thus, it can be a strong candidate for various image retrieval related applications.

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

    PubMed

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

    2010-01-01

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

  1. Phase retrieval and 3D imaging in gold nanoparticles based fluorescence microscopy (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Ilovitsh, Tali; Ilovitsh, Asaf; Weiss, Aryeh M.; Meir, Rinat; Zalevsky, Zeev

    2017-02-01

    Optical sectioning microscopy can provide highly detailed three dimensional (3D) images of biological samples. However, it requires acquisition of many images per volume, and is therefore time consuming, and may not be suitable for live cell 3D imaging. We propose the use of the modified Gerchberg-Saxton phase retrieval algorithm to enable full 3D imaging of gold nanoparticles tagged sample using only two images. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. The proposed concept is then further enhanced also for tracking of single fluorescent particles within a three dimensional (3D) cellular environment based on image processing algorithms that can significantly increases localization accuracy of the 3D point spread function in respect to regular Gaussian fitting. All proposed concepts are validated both on simulated data as well as experimentally.

  2. 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.

  3. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Near Shamrock, Texas Photo Date: May 16, 1977 Credit: NOAA Photo Library, NOAA Central Library

  4. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Union City, Oklahoma Photo Date: May 24, 1973 Credit: NOAA Photo Library, NOAA Central Library

  5. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Near Mayfield, Oklahoma Photo Date: May 16, 1977 Credit: NOAA Photo Library, NOAA Central Library

  6. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Location: Near Lakeview, Texas Photo Date: April 19, 1977 Credit: NOAA Photo Library, NOAA Central Library

  7. Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

    NASA Astrophysics Data System (ADS)

    Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

    2017-07-01

    Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels

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

    SciTech Connect

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

    Two spectrally calibrated tarpaulins (tarps) were co-located at a fixed Global Positioning System (GPS) position on the gravel antenna field at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. Their placement was timed to coincide with the overflight of a new hyperspectral imaging satellite. The intention was to provide an analysis of the data obtained, including the measured and retrieved spectral albedos for the calibration tarps. Subsequently, a full suite of retrieved values of H2O column, and the aerosol overburden, were to be compared to those determined by alternate SGPmore » ground truth assets. To the extent possible, the down-looking cloud images would be assessed against the all-sky images. Because cloud contamination above a certain level precludes the inversion processing of the satellite data, coupled with infrequent targeting opportunities, clear-sky conditions were imposed. The SGP site was chosen not only as a target of opportunity for satellite validation, but as perhaps the best coincident field measurement site, as established by DOE’s ARM Facility. The satellite team had every expectation of using the information obtained from the SGP to improve the inversion products for all subsequent satellite images, including the cloud and radiative models and parameterizations and, thereby, the performance assessment for subsequent and historic image collections. Coordinating with the SGP onsite team, four visits, all in 2009, to the Central Facility occurred: • June 6-8 (successful exploratory visit to plan tarp placements, etc.) • July 18-24 (canceled because of forecast for heavy clouds) • Sep 9-12 (ground tarps placed, onset of clouds) • Nov 7-9 (visit ultimately canceled because of weather predictions). As noted, in each instance, any significant overcast prediction precluded image collection from the satellite. Given the long task

  9. A mobile unit for memory retrieval in daily life based on image and sensor processing

    NASA Astrophysics Data System (ADS)

    Takesumi, Ryuji; Ueda, Yasuhiro; Nakanishi, Hidenobu; Nakamura, Atsuyoshi; Kakimori, Nobuaki

    2003-10-01

    We developed a Mobile Unit which purpose is to support memory retrieval of daily life. In this paper, we describe the two characteristic factors of this unit. (1)The behavior classification with an acceleration sensor. (2)Extracting the difference of environment with image processing technology. In (1), By analyzing power and frequency of an acceleration sensor which turns to gravity direction, the one's activities can be classified using some techniques to walk, stay, and so on. In (2), By extracting the difference between the beginning scene and the ending scene of a stay scene with image processing, the result which is done by user is recognized as the difference of environment. Using those 2 techniques, specific scenes of daily life can be extracted, and important information at the change of scenes can be realized to record. Especially we describe the effect to support retrieving important things, such as a thing left behind and a state of working halfway.

  10. Multispectral Wavefronts Retrieval in Digital Holographic Three-Dimensional Imaging Spectrometry

    NASA Astrophysics Data System (ADS)

    Yoshimori, Kyu

    2010-04-01

    This paper deals with a recently developed passive interferometric technique for retrieving a set of spectral components of wavefronts that are propagating from a spatially incoherent, polychromatic object. The technique is based on measurement of 5-D spatial coherence function using a suitably designed interferometer. By applying signal processing, including aperture synthesis and spectral decomposition, one may obtains a set of wavefronts of different spectral bands. Since each wavefront is equivalent to the complex Fresnel hologram at a particular spectrum of the polychromatic object, application of the conventional Fresnel transform yields 3-D image of different spectrum. Thus, this technique of multispectral wavefronts retrieval provides a new type of 3-D imaging spectrometry based on a fully passive interferometry. Experimental results are also shown to demonstrate the validity of the method.

  11. Development of an Aerosol Opacity Retrieval Algorithm for Use with Multi-Angle Land Surface Images

    NASA Technical Reports Server (NTRS)

    Diner, D.; Paradise, S.; Martonchik, J.

    1994-01-01

    In 1998, the Multi-angle Imaging SpectroRadiometer (MISR) will fly aboard the EOS-AM1 spacecraft. MISR will enable unique methods for retrieving the properties of atmospheric aerosols, by providing global imagery of the Earth at nine viewing angles in four visible and near-IR spectral bands. As part of the MISR algorithm development, theoretical methods of analyzing multi-angle, multi-spectral data are being tested using images acquired by the airborne Advanced Solid-State Array Spectroradiometer (ASAS). In this paper we derive a method to be used over land surfaces for retrieving the change in opacity between spectral bands, which can then be used in conjunction with an aerosol model to derive a bound on absolute opacity.

  12. Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

    NASA Astrophysics Data System (ADS)

    Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2017-09-01

    A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

  13. Global Interior Robot Localisation by a Colour Content Image Retrieval System

    NASA Astrophysics Data System (ADS)

    Chaari, A.; Lelandais, S.; Montagne, C.; Ahmed, M. Ben

    2007-12-01

    We propose a new global localisation approach to determine a coarse position of a mobile robot in structured indoor space using colour-based image retrieval techniques. We use an original method of colour quantisation based on the baker's transformation to extract a two-dimensional colour pallet combining as well space and vicinity-related information as colourimetric aspect of the original image. We conceive several retrieving approaches bringing to a specific similarity measure [InlineEquation not available: see fulltext.] integrating the space organisation of colours in the pallet. The baker's transformation provides a quantisation of the image into a space where colours that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image. Whereas the distance [InlineEquation not available: see fulltext.] provides for partial invariance to translation, sight point small changes, and scale factor. In addition to this study, we developed a hierarchical search module based on the logic classification of images following rooms. This hierarchical module reduces the searching indoor space and ensures an improvement of our system performances. Results are then compared with those brought by colour histograms provided with several similarity measures. In this paper, we focus on colour-based features to describe indoor images. A finalised system must obviously integrate other type of signature like shape and texture.

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

    NASA Astrophysics Data System (ADS)

    Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

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

  15. Image multiplexing and authentication based on double phase retrieval in fresnel transform domain

    NASA Astrophysics Data System (ADS)

    Chang, Hsuan-Ting; Lin, Che-Hsian; Chen, Chien-Yue

    2017-04-01

    An image multiplexing and authentication method based on the double-phase retrieval algorithm (DPRA) with the manipulations of wavelength and position in the Fresnel transform (FrT) domain is proposed in this study. The DPRA generates two matched phase-only functions (POFs) in the different planes so that the corresponding image can be reconstructed at the output plane. Given a number of target images, all the sets of matched POFs are used to generate the phase-locked system through the phase modulation and synthesis to achieve the multiplexing purpose. To reconstruct a target image, the corresponding phase key and all the correct parameters in the FrT are required. Therefore, the authentication system with high-level security can be achieved. The computer simulation verifies the validity of the proposed method and also shows good resistance to the crosstalk among the reconstructed images.

  16. Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

    NASA Technical Reports Server (NTRS)

    Taylor, Jaime R.

    2003-01-01

    NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

  17. Unified modeling language and design of a case-based retrieval system in medical imaging.

    PubMed Central

    LeBozec, C.; Jaulent, M. C.; Zapletal, E.; Degoulet, P.

    1998-01-01

    One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users. Images Figure 6 Figure 7 PMID:9929346

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

    PubMed Central

    2013-01-01

    The figures included in many of the biomedical publications play an important role in understanding the biological experiments and facts described within. Recent studies have shown that it is possible to integrate the information that is extracted from figures in classical document classification and retrieval tasks in order to improve their accuracy. One important observation about the figures included in biomedical publications is that they are often composed of multiple subfigures or panels, each describing different methodologies or results. The use of these multimodal figures is a common practice in bioscience, as experimental results are graphically validated via multiple methodologies or procedures. Thus, for a better use of multimodal figures in document classification or retrieval tasks, as well as for providing the evidence source for derived assertions, it is important to automatically segment multimodal figures into subfigures and panels. This is a challenging task, however, as different panels can contain similar objects (i.e., barcharts and linecharts) with multiple layouts. Also, certain types of biomedical figures are text-heavy (e.g., DNA sequences and protein sequences images) and they differ from traditional images. As a result, classical image segmentation techniques based on low-level image features, such as edges or color, are not directly applicable to robustly partition multimodal figures into single modal panels. In this paper, we describe a robust solution for automatically identifying and segmenting unimodal panels from a multimodal figure. Our framework starts by robustly harvesting figure-caption pairs from biomedical articles. We base our approach on the observation that the document layout can be used to identify encoded figures and figure boundaries within PDF files. Taking into consideration the document layout allows us to correctly extract figures from the PDF document and associate their corresponding caption. We combine pixel

  19. Photo-oxidative stress in emerging and senescing leaves: a mirror image?

    PubMed

    Juvany, Marta; Müller, Maren; Munné-Bosch, Sergi

    2013-08-01

    The life cycle of a leaf can be characterized as consisting of different stages: from primordial leaf initiation in the shoot apical meristem (SAM) to leaf senescence. Leaf development, from early leaf growth to senescence, is tightly controlled by plant development and the environment. Here, we primarily focus on summarizing current evidence indicating that photo-oxidative stress occurs at the two extremes of a leaf's lifespan. Some recent studies clearly indicate that--as happens in senescing leaves--emerging new leaves suffer from photo-oxidative stress, which suggests that oxidative stress plays a key role at both ends of the leaf life cycle. We discuss the causes and consequences of suffering from photo-oxidative stress during leaf development, paying attention to the particularities of this process at the two extremes of leaf development. Of particular importance is the current evidence showing mechanisms that maintain an adequate cellular reactive oxygen species/antioxidant (redox) balance that allows growth and prevents oxidative damage in young emerging leaves, while later on photo-oxidative stress induces cell death in senescing leaves. Also of interest is the fact that reductions in the efficiency of photosystem II photochemistry may not necessarily indicate photo-oxidative stress in emerging leaves. In this review, we summarize current knowledge of photoinhibition, photoprotection, and photo-oxidative stress at the two ends of the leaf life cycle: early leaf growth and leaf senescence.

  20. Exploring access to scientific literature using content-based image retrieval

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  1. Vaccine-Preventable Disease Photos

    MedlinePlus

    ... Typhoid fever HPV Polio Whooping cough Influenza (flu) Rabies Yellow fever Photo Library Photographs accompanied by text ... images Pneumococcus Three images Polio Twenty-six images Rabies Ten images Rotavirus Two images Rubella Fifteen images ...

  2. 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.

  3. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    SciTech Connect

    Wu, Zhao; Gao, Kun; Chen, Jian

    2015-02-15

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using themore » error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.« less

  4. Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

    NASA Astrophysics Data System (ADS)

    Li, Qingliang; Shi, Weili; Yang, Huamin; Zhang, Huimao; Li, Guoxin; Chen, Tao; Mori, Kensaku; Jiang, Zhengang

    2017-03-01

    Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.

  5. A new approach for fast indexing of hyperspectral image data for knowledge retrieval and mining

    NASA Astrophysics Data System (ADS)

    Clowers, Robert; Dua, Sumeet

    2005-11-01

    Multispectral sensors produce images with a few relatively broad wavelength bands. Hyperspectral remote sensors, on the other hand, collect image data simultaneously in dozens or hundreds of narrow and adjacent spectral bands. These measurements make it possible to derive a continuous spectrum for each image cell, generating an image cube across multiple spectral components. Hyperspectral imaging has sound applications in a variety of areas such as mineral exploration, hazardous waste remediation, mapping habitat, invasive vegetation, eco system monitoring, hazardous gas detection, mineral detection, soil degradation, and climate change. This image has a strong potential for transforming the imaging paradigms associated with several design and manufacturing processes. In this paper, we describe a novel approach for fast indexing of multi-dimensional hyperspectral image data, especially for data mining applications. The index exploits the spectral and spatial relationships embedded in these image sets. The index will be employed for knowledge retrieval applications that require fast information interpretation approaches. The index can also be deployed in real-time mission-critical domains, as it is shown to exhibit speed with high degrees of dimensionality associated with the data. The strength of this index in terms of degree of false dismissals and false alarms will also be demonstrated. The paper will highlight some common applications of this imaging computational paradigm and will conclude with directions for future improvement and investigation.

  6. A novel method for efficient archiving and retrieval of biomedical images using MPEG-7

    NASA Astrophysics Data System (ADS)

    Meyer, Joerg; Pahwa, Ash

    2004-10-01

    Digital archiving and efficient retrieval of radiological scans have become critical steps in contemporary medical diagnostics. Since more and more images and image sequences (single scans or video) from various modalities (CT/MRI/PET/digital X-ray) are now available in digital formats (e.g., DICOM-3), hospitals and radiology clinics need to implement efficient protocols capable of managing the enormous amounts of data generated daily in a typical clinical routine. We present a method that appears to be a viable way to eliminate the tedious step of manually annotating image and video material for database indexing. MPEG-7 is a new framework that standardizes the way images are characterized in terms of color, shape, and other abstract, content-related criteria. A set of standardized descriptors that are automatically generated from an image is used to compare an image to other images in a database, and to compute the distance between two images for a given application domain. Text-based database queries can be replaced with image-based queries using MPEG-7. Consequently, image queries can be conducted without any prior knowledge of the keys that were used as indices in the database. Since the decoding and matching steps are not part of the MPEG-7 standard, this method also enables searches that were not planned by the time the keys were generated.

  7. Target-oriented retrieval of subsurface wave fields - Pushing the resolution limits in seismic imaging

    NASA Astrophysics Data System (ADS)

    Vasconcelos, Ivan; Ozmen, Neslihan; van der Neut, Joost; Cui, Tianci

    2017-04-01

    Travelling wide-bandwidth seismic waves have long been used as a primary tool in exploration seismology because they can probe the subsurface over large distances, while retaining relatively high spatial resolution. The well-known Born resolution limit often seems to be the lower bound on spatial imaging resolution in real life examples. In practice, data acquisition cost, time constraints and other factors can worsen the resolution achieved by wavefield imaging. Could we obtain images whose resolution beats the Born limits? Would it be practical to achieve it, and what are we missing today to achieve this? In this talk, we will cover aspects of linear and nonlinear seismic imaging to understand elements that play a role in obtaining "super-resolved" seismic images. New redatuming techniques, such as the Marchenko method, enable the retrieval of subsurface fields that include multiple scattering interactions, while requiring relatively little knowledge of model parameters. Together with new concepts in imaging, such as Target-Enclosing Extended Images, these new redatuming methods enable new targeted imaging frameworks. We will make a case as to why target-oriented approaches to reconstructing subsurface-domain wavefields from surface data may help in increasing the resolving power of seismic imaging, and in pushing the limits on parameter estimation. We will illustrate this using a field data example. Finally, we will draw connections between seismic and other imaging modalities, and discuss how this framework could be put to use in other applications

  8. Plant leaf chlorophyll content retrieval based on a field imaging spectroscopy system.

    PubMed

    Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

    2014-10-23

    A field imaging spectrometer system (FISS; 380-870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%-35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector.

  9. Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System

    PubMed Central

    Liu, Bo; Yue, Yue-Min; Li, Ru; Shen, Wen-Jing; Wang, Ke-Lin

    2014-01-01

    A field imaging spectrometer system (FISS; 380–870 nm and 344 bands) was designed for agriculture applications. In this study, FISS was used to gather spectral information from soybean leaves. The chlorophyll content was retrieved using a multiple linear regression (MLR), partial least squares (PLS) regression and support vector machine (SVM) regression. Our objective was to verify the performance of FISS in a quantitative spectral analysis through the estimation of chlorophyll content and to determine a proper quantitative spectral analysis method for processing FISS data. The results revealed that the derivative reflectance was a more sensitive indicator of chlorophyll content and could extract content information more efficiently than the spectral reflectance, which is more significant for FISS data compared to ASD (analytical spectral devices) data, reducing the corresponding RMSE (root mean squared error) by 3.3%–35.6%. Compared with the spectral features, the regression methods had smaller effects on the retrieval accuracy. A multivariate linear model could be the ideal model to retrieve chlorophyll information with a small number of significant wavelengths used. The smallest RMSE of the chlorophyll content retrieved using FISS data was 0.201 mg/g, a relative reduction of more than 30% compared with the RMSE based on a non-imaging ASD spectrometer, which represents a high estimation accuracy compared with the mean chlorophyll content of the sampled leaves (4.05 mg/g). Our study indicates that FISS could obtain both spectral and spatial detailed information of high quality. Its image-spectrum-in-one merit promotes the good performance of FISS in quantitative spectral analyses, and it can potentially be widely used in the agricultural sector. PMID:25341439

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

    NASA Astrophysics Data System (ADS)

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

    2003-05-01

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

  11. Retrievals of atmospheric variables on the gas giants from ground-based mid-infrared imaging

    NASA Astrophysics Data System (ADS)

    Fletcher, L. N.; Orton, G. S.; Yanamandra-Fisher, P.; Fisher, B. M.; Parrish, P. D.; Irwin, P. G. J.

    2009-03-01

    Thermal-infrared imaging of Jupiter and Saturn using the NASA/IRTF and Subaru observatories are quantitatively analyzed to assess the capabilities for reproducing and extending the zonal mean atmospheric results of the Cassini/CIRS experiment. We describe the development of a robust, systematic and reproducible approach to the acquisition and reduction of planetary images in the mid-infrared (7-25 μm), and perform an adaptation and validation of the optimal estimation, correlated- k retrieval algorithm described by Irwin et al. [Irwin, P., Teanby, N., de Kok, R., Fletcher, L., Howett, C., Tsang, C., Wilson, C., Calcutt, S., Nixon, C., Parrish, P., 2008. J. Quant. Spectrosc. Radiat. Trans. 109 (6), 1136-1150] for channel-integrated radiances. Synthetic spectral analyses and a comparison to Cassini results are used to verify our abilities to retrieve temperatures, haze opacities and gaseous abundances from filtered imaging. We find that ground-based imaging with a sufficiently high spatial resolution is able to reproduce the three-dimensional temperature and para-H 2 fields measured by spacecraft visiting Jupiter and Saturn, allowing us to investigate vertical wind shear, pressure and, with measured cloud-top winds, Ertel potential vorticity on potential temperature surfaces. Furthermore, by scaling vertical profiles of NH 3, PH 3, haze opacity and hydrocarbons as free parameters during thermal retrievals, we can produce meridional results comparable with CIRS spectroscopic investigations. This paper demonstrates that mid-IR imaging instruments operating at ground-based observatories have access to several dynamical and chemical diagnostics of the atmospheric state of the gas giants, offering the prospect for quantitative studies over much longer baselines and often covering much wider areas than is possible from spaceborne platforms.

  12. Mining biomedical images towards valuable information retrieval in biomedical and life sciences

    PubMed Central

    Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

    2016-01-01

    Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. PMID:27538578

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

    PubMed

    Maragoudakis, Manolis; Maglogiannis, Ilias

    2011-06-01

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

  14. Mining biomedical images towards valuable information retrieval in biomedical and life sciences.

    PubMed

    Ahmed, Zeeshan; Zeeshan, Saman; Dandekar, Thomas

    2016-01-01

    Biomedical images are helpful sources for the scientists and practitioners in drawing significant hypotheses, exemplifying approaches and describing experimental results in published biomedical literature. In last decades, there has been an enormous increase in the amount of heterogeneous biomedical image production and publication, which results in a need for bioimaging platforms for feature extraction and analysis of text and content in biomedical images to take advantage in implementing effective information retrieval systems. In this review, we summarize technologies related to data mining of figures. We describe and compare the potential of different approaches in terms of their developmental aspects, used methodologies, produced results, achieved accuracies and limitations. Our comparative conclusions include current challenges for bioimaging software with selective image mining, embedded text extraction and processing of complex natural language queries. © The Author(s) 2016. Published by Oxford University Press.

  15. Using complex networks towards information retrieval and diagnostics in multidimensional imaging.

    PubMed

    Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

    2015-12-02

    We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

  16. Using complex networks towards information retrieval and diagnostics in multidimensional imaging

    PubMed Central

    Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

    2015-01-01

    We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers. PMID:26626047

  17. Using complex networks towards information retrieval and diagnostics in multidimensional imaging

    NASA Astrophysics Data System (ADS)

    Banerjee, Soumya Jyoti; Azharuddin, Mohammad; Sen, Debanjan; Savale, Smruti; Datta, Himadri; Dasgupta, Anjan Kr; Roy, Soumen

    2015-12-01

    We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

  18. Unified modeling language and design of a case-based retrieval system in medical imaging.

    PubMed

    LeBozec, C; Jaulent, M C; Zapletal, E; Degoulet, P

    1998-01-01

    One goal of artificial intelligence research into case-based reasoning (CBR) systems is to develop approaches for designing useful and practical interactive case-based environments. Explaining each step of the design of the case-base and of the retrieval process is critical for the application of case-based systems to the real world. We describe herein our approach to the design of IDEM--Images and Diagnosis from Examples in Medicine--a medical image case-based retrieval system for pathologists. Our approach is based on the expressiveness of an object-oriented modeling language standard: the Unified Modeling Language (UML). We created a set of diagrams in UML notation illustrating the steps of the CBR methodology we used. The key aspect of this approach was selecting the relevant objects of the system according to user requirements and making visualization of cases and of the components of the case retrieval process. Further evaluation of the expressiveness of the design document is required but UML seems to be a promising formalism, improving the communication between the developers and users.

  19. Novel Fourier-domain constraint for fast phase retrieval in coherent diffraction imaging.

    PubMed

    Latychevskaia, Tatiana; Longchamp, Jean-Nicolas; Fink, Hans-Werner

    2011-09-26

    Coherent diffraction imaging (CDI) for visualizing objects at atomic resolution has been realized as a promising tool for imaging single molecules. Drawbacks of CDI are associated with the difficulty of the numerical phase retrieval from experimental diffraction patterns; a fact which stimulated search for better numerical methods and alternative experimental techniques. Common phase retrieval methods are based on iterative procedures which propagate the complex-valued wave between object and detector plane. Constraints in both, the object and the detector plane are applied. While the constraint in the detector plane employed in most phase retrieval methods requires the amplitude of the complex wave to be equal to the squared root of the measured intensity, we propose a novel Fourier-domain constraint, based on an analogy to holography. Our method allows achieving a low-resolution reconstruction already in the first step followed by a high-resolution reconstruction after further steps. In comparison to conventional schemes this Fourier-domain constraint results in a fast and reliable convergence of the iterative reconstruction process. © 2011 Optical Society of America

  20. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image - spac0020 ESSA I, a TIROS cartwheel satellite launched on February 3, 1966. Image ID: spac0020, NOAA In

  1. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image -Welt...." by Erasmus Francisci, 1680. Library Call Number QC859 .F72 1680. Image ID: wea02217

  2. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image ] unserer Nider-Welt...." by Erasmus Francisci, 1680. Library Call Number QC859 .F72 1680. Image ID

  3. Amphetamine Fails to Alter Cued Recollection of Emotional Images: Study of Encoding, Retrieval, and State-Dependency

    PubMed Central

    Weafer, Jessica; Gallo, David A.; de Wit, Harriet

    2014-01-01

    Stimulant drugs facilitate both encoding and retrieval of salient information in laboratory animals, but less is known about their effects on memory for emotionally salient visual images in humans. The current study investigated dextroamphetamine (AMP) effects on memory for emotional pictures in healthy humans, by administering the drug only at encoding, only at retrieval, or at both encoding and retrieval. During the encoding session, all participants viewed standardized positive, neutral, and negative pictures from the International Affective Picture System (IAPS). 48 hours later they attended a retrieval session testing their cued recollection of these stimuli. Participants were randomly assigned to one of four conditions (N = 20 each): condition AP (20 mg AMP at encoding and placebo (PL) at retrieval); condition PA (PL at encoding and AMP at retrieval); condition AA (AMP at encoding and retrieval); or condition PP (PL at encoding and retrieval). Amphetamine produced its expected effects on physiological and subjective measures, and negative pictures were recollected more frequently than neutral pictures. However, contrary to hypotheses, AMP did not affect recollection for positive, negative, or neutral stimuli, whether it was administered at encoding, retrieval, or at both encoding and retrieval. Moreover, recollection accuracy was not state-dependent. Considered in light of other recent drug studies in humans, this study highlights the sensitivity of drug effects to memory testing conditions and suggests future strategies for translating preclinical findings to human behavioral laboratories. PMID:24587355

  4. Amphetamine fails to alter cued recollection of emotional images: study of encoding, retrieval, and state-dependency.

    PubMed

    Weafer, Jessica; Gallo, David A; de Wit, Harriet

    2014-01-01

    Stimulant drugs facilitate both encoding and retrieval of salient information in laboratory animals, but less is known about their effects on memory for emotionally salient visual images in humans. The current study investigated dextroamphetamine (AMP) effects on memory for emotional pictures in healthy humans, by administering the drug only at encoding, only at retrieval, or at both encoding and retrieval. During the encoding session, all participants viewed standardized positive, neutral, and negative pictures from the International Affective Picture System (IAPS). 48 hours later they attended a retrieval session testing their cued recollection of these stimuli. Participants were randomly assigned to one of four conditions (N=20 each): condition AP (20 mg AMP at encoding and placebo (PL) at retrieval); condition PA (PL at encoding and AMP at retrieval); condition AA (AMP at encoding and retrieval); or condition PP (PL at encoding and retrieval). Amphetamine produced its expected effects on physiological and subjective measures, and negative pictures were recollected more frequently than neutral pictures. However, contrary to hypotheses, AMP did not affect recollection for positive, negative, or neutral stimuli, whether it was administered at encoding, retrieval, or at both encoding and retrieval. Moreover, recollection accuracy was not state-dependent. Considered in light of other recent drug studies in humans, this study highlights the sensitivity of drug effects to memory testing conditions and suggests future strategies for translating preclinical findings to human behavioral laboratories.

  5. Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

    NASA Astrophysics Data System (ADS)

    Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

    2015-09-01

    In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

  6. Noniterative approach to the missing data problem in coherent diffraction imaging by phase retrieval.

    PubMed

    Nakajima, Nobuharu

    2010-07-20

    When a very intense beam is used for illuminating an object in coherent x-ray diffraction imaging, the intensities at the center of the diffraction pattern for the object are cut off by a beam stop that is utilized to block the intense beam. Until now, only iterative phase-retrieval methods have been applied to object reconstruction from a single diffraction pattern with a deficiency of central data due to a beam stop. As an alternative method, I present a noniterative solution in which an interpolation method based on the sampling theorem for the missing data is used for object reconstruction with our previously proposed phase-retrieval method using an aperture-array filter. Computer simulations demonstrate the reconstruction of a complex-amplitude object from a single diffraction pattern with a missing data area, which is generally difficult to treat with the iterative methods because a nonnegativity constraint cannot be used for such an object.

  7. Retrieval of Ocean Surface Windspeed and Rainrate from the Hurricane Imaging Radiometer (HIRAD) Brightness Temperature Observations

    NASA Technical Reports Server (NTRS)

    Biswas, Sayak K.; Jones, Linwood; Roberts, Jason; Ruf, Christopher; Ulhorn, Eric; Miller, Timothy

    2012-01-01

    The Hurricane Imaging Radiometer (HIRAD) is a new airborne synthetic aperture passive microwave radiometer capable of wide swath imaging of the ocean surface wind speed under heavy precipitation e.g. in tropical cyclones. It uses interferometric signal processing to produce upwelling brightness temperature (Tb) images at its four operating frequencies 4, 5, 6 and 6.6 GHz [1,2]. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during 2010 as its first science field campaign. It produced Tb images with 70 km swath width and 3 km resolution from a 20 km altitude. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The column averaged liquid water then could be related to an average rain rate. The retrieval algorithm (and the HIRAD instrument itself) is a direct descendant of the nadir-only Stepped Frequency Microwave Radiometer that is used operationally by the NOAA Hurricane Research Division to monitor tropical cyclones [3,4]. However, due to HIRAD s slant viewing geometry (compared to nadir viewing SFMR) a major modification is required in the algorithm. Results based on the modified algorithm from the GRIP campaign will be presented in the paper.

  8. Annotating image ROIs with text descriptions for multimodal biomedical document retrieval

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Regions of interest (ROIs) that are pointed to by overlaid markers (arrows, asterisks, etc.) in biomedical images are expected to contain more important and relevant information than other regions for biomedical article indexing and retrieval. We have developed several algorithms that localize and extract the ROIs by recognizing markers on images. Cropped ROIs then need to be annotated with contents describing them best. In most cases accurate textual descriptions of the ROIs can be found from figure captions, and these need to be combined with image ROIs for annotation. The annotated ROIs can then be used to, for example, train classifiers that separate ROIs into known categories (medical concepts), or to build visual ontologies, for indexing and retrieval of biomedical articles. We propose an algorithm that pairs visual and textual ROIs that are extracted from images and figure captions, respectively. This algorithm based on dynamic time warping (DTW) clusters recognized pointers into groups, each of which contains pointers with identical visual properties (shape, size, color, etc.). Then a rule-based matching algorithm finds the best matching group for each textual ROI mention. Our method yields a precision and recall of 96% and 79%, respectively, when ground truth textual ROI data is used.

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

    NASA Astrophysics Data System (ADS)

    Masseroli, Marco; Pinciroli, Francesco

    2000-12-01

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

  10. Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

    PubMed

    Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

    2011-11-01

    Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

  11. Active imaging with the aids of polarization retrieve in turbid media system

    NASA Astrophysics Data System (ADS)

    Tao, Qiangqiang; Sun, Yongxuan; Shen, Fei; Xu, Qiang; Gao, Jun; Guo, Zhongyi

    2016-01-01

    We propose a novel active imaging based on the polarization retrieve (PR) method in turbid media system. In our simulations, the Monte Carlo (MC) algorithm has been used to investigate the scattering process between the incident photons and the scattering particles, and the visually concordant object but with different polarization characteristics in different regions, has been selected as the original target that is placed in the turbid media. Under linearly and circularly polarized illuminations, the simulation results demonstrate that the corresponding polarization properties can provide additional information for the imaging, and the contrast of the polarization image can also be enhanced greatly compared to the simplex intensity image in the turbid media. Besides, the polarization image adjusted by the PR method can further enhance the visibility and contrast. In addition, by PR imaging method, with the increasing particles' size in Mie's scale, the visibility can be enhanced, because of the increased forward scattering effect. In general, in the same circumstance, the circular polarization images can offer a better contrast and visibility than that of linear ones. The results indicate that the PR imaging method is more applicable to the scattering media system with relatively larger particles such as aerosols, heavy fog, cumulus, and seawater, as well as to biological tissues and blood media.

  12. 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.

  13. Image retrieval and processing system version 2.0 development work

    NASA Technical Reports Server (NTRS)

    Slavney, Susan H.; Guinness, Edward A.

    1991-01-01

    The Image Retrieval and Processing System (IRPS) is a software package developed at Washington University and used by the NASA Regional Planetary Image Facilities (RPIF's). The IRPS combines data base management and image processing components to allow the user to examine catalogs of image data, locate the data of interest, and perform radiometric and geometric calibration of the data in preparation for analysis. Version 1.0 of IRPS was completed in Aug. 1989 and was installed at several IRPS's. Other RPIF's use remote logins via NASA Science Internet to access IRPS at Washington University. Work was begun on designing and population a catalog of Magellan image products that will be part of IRPS Version 2.0, planned for release by the end of calendar year 1991. With this catalog, a user will be able to search by orbit and by location for Magellan Basic Image Data Records (BIDR's), Mosaicked Image Data Records (MIDR's), and Altimetry-Radiometry Composite Data Records (ARCDR's). The catalog will include the Magellan CD-ROM volume, director, and file name for each data product. The image processing component of IRPS is based on the Planetary Image Cartography Software (PICS) developed by the U.S. Geological Survey, Flagstaff, Arizona. To augment PICS capabilities, a set of image processing programs were developed that are compatible with PICS-format images. This software includes general-purpose functions that PICS does not have, analysis and utility programs for specific data sets, and programs from other sources that were modified to work with PICS images. Some of the software will be integrated into the Version 2.0 release of IRPS. A table is presented that lists the programs with a brief functional description of each.

  14. Event recognition in personal photo collections via multiple instance learning-based classification of multiple images

    NASA Astrophysics Data System (ADS)

    Ahmad, Kashif; Conci, Nicola; Boato, Giulia; De Natale, Francesco G. B.

    2017-11-01

    Over the last few years, a rapid growth has been witnessed in the number of digital photos produced per year. This rapid process poses challenges in the organization and management of multimedia collections, and one viable solution consists of arranging the media on the basis of the underlying events. However, album-level annotation and the presence of irrelevant pictures in photo collections make event-based organization of personal photo albums a more challenging task. To tackle these challenges, in contrast to conventional approaches relying on supervised learning, we propose a pipeline for event recognition in personal photo collections relying on a multiple instance-learning (MIL) strategy. MIL is a modified form of supervised learning and fits well for such applications with weakly labeled data. The experimental evaluation of the proposed approach is carried out on two large-scale datasets including a self-collected and a benchmark dataset. On both, our approach significantly outperforms the existing state-of-the-art.

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  16. A fast image retrieval method based on SVM and imbalanced samples in filtering multimedia message spam

    NASA Astrophysics Data System (ADS)

    Chen, Zhang; Peng, Zhenming; Peng, Lingbing; Liao, Dongyi; He, Xin

    2011-11-01

    With the swift and violent development of the Multimedia Messaging Service (MMS), it becomes an urgent task to filter the Multimedia Message (MM) spam effectively in real-time. For the fact that most MMs contain images or videos, a method based on retrieving images is given in this paper for filtering MM spam. The detection method used in this paper is a combination of skin-color detection, texture detection, and face detection, and the classifier for this imbalanced problem is a very fast multi-classification combining Support vector machine (SVM) with unilateral binary decision tree. The experiments on 3 test sets show that the proposed method is effective, with the interception rate up to 60% and the average detection time for each image less than 1 second.

  17. A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2013-01-01

    Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

  18. Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

    NASA Technical Reports Server (NTRS)

    Jacob, Maria; Salemirad, Matin; Jones, W. Linwood; Biswas, Sayak; Cecil, Daniel

    2015-01-01

    On board of the NASA's Global Hawk (AV1) aircraft there are two microwave, namely: the passive microwave Hurricane Imaging Radiometer (HIRAD), and the active microwave High-altitude Imaging Wind and Rain Airborne Profiler (HIWRAP). This paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when the Global Hawk aircraft flew over an intense tropical squall-line that was simultaneously observed, by the Tampa NEXRAD meteorological radar. During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. NEXRAD 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. In this paper, results are presented of the three-way inter-comparison of HIRAD Tb, HIWRAP dbZ and NEXRAD rain rate imagery.

  19. Attention-based image similarity measure with application to content-based information retrieval

    NASA Astrophysics Data System (ADS)

    Stentiford, Fred W. M.

    2003-01-01

    Whilst storage and capture technologies are able to cope with huge numbers of images, image retrieval is in danger of rendering many repositories valueless because of the difficulty of access. This paper proposes a similarity measure that imposes only very weak assumptions on the nature of the features used in the recognition process. This approach does not make use of a pre-defined set of feature measurements which are extracted from a query image and used to match those from database images, but instead generates features on a trial and error basis during the calculation of the similarity measure. This has the significant advantage that features that determine similarity can match whatever image property is important in a particular region whether it be a shape, a texture, a colour or a combination of all three. It means that effort is expended searching for the best feature for the region rather than expecting that a fixed feature set will perform optimally over the whole area of an image and over every image in a database. The similarity measure is evaluated on a problem of distinguishing similar shapes in sets of black and white symbols.

  20. Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

    PubMed

    Zhang, Yu; Wu, Jianxin; Cai, Jianfei

    2016-05-01

    In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

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

    PubMed

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

    2007-11-01

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

  2. Influence of aerosol estimation on coastal water products retrieved from HICO images

    NASA Astrophysics Data System (ADS)

    Patterson, Karen W.; Lamela, Gia

    2011-06-01

    The Hyperspectral Imager for the Coastal Ocean (HICO) is a hyperspectral sensor which was launched to the International Space Station in September 2009. The Naval Research Laboratory (NRL) has been developing the Coastal Water Signatures Toolkit (CWST) to estimate water depth, bottom type and water column constituents such as chlorophyll, suspended sediments and chromophoric dissolved organic matter from hyperspectral imagery. The CWST uses a look-up table approach, comparing remote sensing reflectance spectra observed in an image to a database of modeled spectra for pre-determined water column constituents, depth and bottom type. In order to successfully use this approach, the remote sensing reflectances must be accurate which implies accurately correcting for the atmospheric contribution to the HICO top of the atmosphere radiances. One tool the NRL is using to atmospherically correct HICO imagery is Correction of Coastal Ocean Atmospheres (COCOA), which is based on Tafkaa 6S. One of the user input parameters to COCOA is aerosol optical depth or aerosol visibility, which can vary rapidly over short distances in coastal waters. Changes to the aerosol thickness results in changes to the magnitude of the remote sensing reflectances. As such, the CWST retrievals for water constituents, depth and bottom type can be expected to vary in like fashion. This work is an illustration of the variability in CWST retrievals due to inaccurate aerosol thickness estimation during atmospheric correction of HICO images.

  3. Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

    PubMed

    ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

    2017-11-01

    Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Data-driven Green's function retrieval and application to imaging with multidimensional deconvolution

    NASA Astrophysics Data System (ADS)

    Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel

    2014-01-01

    An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.

  5. Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

    NASA Astrophysics Data System (ADS)

    Asmat, A.; Jalal, K. A.; Ahmad, N.

    2018-02-01

    The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

  6. Using sparsity information for iterative phase retrieval in x-ray propagation imaging.

    PubMed

    Pein, A; Loock, S; Plonka, G; Salditt, T

    2016-04-18

    For iterative phase retrieval algorithms in near field x-ray propagation imaging experiments with a single distance measurement, it is indispensable to have a strong constraint based on a priori information about the specimen; for example, information about the specimen's support. Recently, Loock and Plonka proposed to use the a priori information that the exit wave is sparsely represented in a certain directional representation system, a so-called shearlet system. In this work, we extend this approach to complex-valued signals by applying the new shearlet constraint to amplitude and phase separately. Further, we demonstrate its applicability to experimental data.

  7. Retrieval of ion distributions in RC from TWINS ENA images by CT technique

    NASA Astrophysics Data System (ADS)

    Ma, S.; Yan, W.; Xu, L.; Goldstein, J.; McComas, D. J.

    2010-12-01

    The Two Wide-angle Imaging Neutral-atom Spectrometers (TWINS) mission is the first constellation to employ imagers on two separate spacecraft to measure energetic neutral atoms (ENA) produced by charge exchange between ring current energetic ions and cold exospheric neutral atoms. By applying the 3-D volumetric pixel (voxel) computed tomography (CT) inversion method to TWINS images, parent ion populations in the ring current (RC) and auroral regions are retrieved from their ENA signals. This methodology is implemented for data obtained during the main phase of a moderate geomagnetic storm on 11 October 2008. For this storm the two TWINS satellites were located in nearly the same meridian plane at vantage points widely separated in magnetic local time, and both more than 5 RE geocentric distance from the Earth. In the retrieval process, the energetic ion fluxes to be retrieved are assumed being isotropic with respect to pitch angle. The ENA data used in this study are differential fluxes averaged over 12 sweeps (corresponding to an interval of 16 min.) at different energy levels ranging throughout the full 1--100 keV energy range of TWINS. The ENA signals have two main components: (1) a low-latitude/ high-altitude signal from trapped RC ions and (2) a low-altitude signal from precipitating ions in the auroral/subauroral ionosphere. In the retrieved ion distributions, the main part of the RC component is located around midnight toward dawn sector with L from 3 to 7 or farther, while the subauroral low-altitude component is mainly at pre-midnight. It seems that the dominant energy of the RC ions for this storm is at the lowest energy level of 1-2 keV, with another important energy band centered about 44 keV. The low-altitude component is consistent with in situ observations by DMSP/SSJ4. The result of this study demonstrates that with satellite constellations such as TWINS, using all-sky ENA imagers deployed at multiple vantage points, 3-D distribution of RC ion

  8. Evaluation of applicability of high-resolution multiangle imaging photo-polarimetric observations for aerosol atmospheric correction

    NASA Astrophysics Data System (ADS)

    Kalashnikova, Olga; Garay, Michael; Xu, Feng; Diner, David; Seidel, Felix

    2016-07-01

    Multiangle spectro-polarimetric measurements have been advocated as an additional tool for better understanding and quantifying the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of this work is the assessment of the effects of absorbing aerosol properties on remote sensing reflectance measurement uncertainty caused by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. In this work a vector Markov Chain radiative transfer code including bio-optical models was used to quantitatively evaluate in water leaving radiances between atmospheres containing realistic UV-enhanced and non-spherical aerosols and the SEADAS carbonaceous and dust-like aerosol models. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach developed for modeling dust for the AERONET network of ground-based sunphotometers. As a next step, we have developed a retrieval code that employs a coupled Markov Chain (MC) and adding/doubling radiative transfer method for joint retrieval of aerosol properties and water leaving radiance from Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) polarimetric observations. The AirMSPI-1 instrument has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI typically acquires observations of a target area at 9 view angles between ±67° at 10 m resolution. AirMSPI spectral channels are centered at 355, 380, 445, 470, 555, 660, and 865 nm, with 470, 660, and 865 reporting linear polarization. We

  9. The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

    2007-01-01

    The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

  10. An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

    NASA Astrophysics Data System (ADS)

    Nouizi, F.; Erkol, H.; Luk, A.; Marks, M.; Unlu, M. B.; Gulsen, G.

    2016-10-01

    We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

  11. A unified framework for image retrieval using keyword and visual features.

    PubMed

    Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

    2005-07-01

    In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

  12. Retrieving the unretrievable in electronic imaging systems: emotions, themes, and stories

    NASA Astrophysics Data System (ADS)

    Joergensen, Corinne

    1999-05-01

    New paradigms such as 'affective computing' and user-based research are extending the realm of facets traditionally addressed in IR systems. This paper builds on previous research reported to the electronic imaging community concerning the need to provide access to more abstract attributes of images than those currently amenable to a variety of content-based and text-based indexing techniques. Empirical research suggest that, for visual materials, in addition to standard bibliographic data and broad subject, and in addition to such visually perceptual attributes such as color, texture, shape, and position or focal point, additional access points such as themes, abstract concepts, emotions, stories, and 'people-related' information such as social status would be useful in image retrieval. More recent research demonstrates that similar results are also obtained with 'fine arts' images, which generally have no access provided for these types of attributes. Current efforts to match image attributes as revealed in empirical research with those addressed both in current textural and content-based indexing systems are discussed, as well as the need for new representations for image attributes and for collaboration among diverse communities of researchers.

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

    PubMed

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

    2012-10-04

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

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

    PubMed Central

    2012-01-01

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

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

    PubMed

    Yang, Mengzhao; Song, Wei; Mei, Haibin

    2017-07-23

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

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

    PubMed Central

    Song, Wei; Mei, Haibin

    2017-01-01

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

  17. Retrieval of long and short lists from long term memory: a functional magnetic resonance imaging study with human subjects.

    PubMed

    Zysset, S; Müller, K; Lehmann, C; Thöne-Otto, A I; von Cramon, D Y

    2001-11-13

    Previous studies have shown that reaction time in an item-recognition task with both short and long lists is a quadratic function of list length. This suggests that either different memory retrieval processes are implied for short and long lists or an adaptive process is involved. An event-related functional magnetic resonance imaging study with nine subjects and list lengths varying between 3 and 18 words was conducted to identify the underlying neuronal structures of retrieval from long and short lists. For the retrieval and processing of word-lists a single fronto-parietal network, including premotor, left prefrontal, left precuneal and left parietal regions, was activated. With increasing list length, no additional regions became involved in retrieving information from long-term memory, suggesting that not necessarily different, but highly adaptive retrieval processes are involved.

  18. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Photographer: Jim Leonard Credit: NOAA Photo Library, NOAA Central Library; OAR/ERL/National Severe Storms

  19. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Ainsworth Credit: NOAA Photo Library, NOAA Central Library; OAR/ERL/National Severe Storms Laboratory (NSSL

  20. Ultrasound-Mediated Biophotonic Imaging: A Review of Acousto-Optical Tomography and Photo-Acoustic Tomography

    PubMed Central

    Wang, Lihong V.

    2004-01-01

    This article reviews two types of ultrasound-mediated biophotonic imaging–acousto-optical tomography (AOT, also called ultrasound-modulated optical tomography) and photo-acoustic tomography (PAT, also called opto-acoustic or thermo-acoustic tomography)–both of which are based on non-ionizing optical and ultrasonic waves. The goal of these technologies is to combine the contrast advantage of the optical properties and the resolution advantage of ultrasound. In these two technologies, the imaging contrast is based primarily on the optical properties of biological tissues, and the imaging resolution is based primarily on the ultrasonic waves that either are provided externally or produced internally, within the biological tissues. In fact, ultrasonic mediation overcomes both the resolution disadvantage of pure optical imaging in thick tissues and the contrast and speckle disadvantages of pure ultrasonic imaging. In our discussion of AOT, the relationship between modulation depth and acoustic amplitude is clarified. Potential clinical applications of ultrasound-mediated biophotonic imaging include early cancer detection, functional imaging, and molecular imaging. PMID:15096709

  1. Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

    PubMed

    Depeursinge, Adrien; Vargas, Alejandro; Gaillard, Frédéric; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

    2012-01-01

    Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed. Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases. In a first step, the proposed system shows a three-dimensional map of categorized lung tissue patterns with quantification of the diseases based on texture analysis of the lung parenchyma. Then, based on the proportions of abnormal and normal lung tissue as well as clinical data of the patients, retrieval of similar cases is enabled using a multimodal distance aggregating content-based image retrieval (CBIR) and text-based information search. The global system leads to a hybrid detection-CBIR-based CAD, where detection-based and CBIR-based CAD show to be complementary both on the user's side and on the algorithmic side. The proposed approach is in accordance with the classical workflow of clinicians searching for similar cases in textbooks and personal collections. The developed system enables objective and customizable inter-case similarity assessment, and the performance measures obtained with a leave-one-patient-out cross-validation (LOPO CV) are representative of a clinical usage of the system.

  2. Skin Parameter Map Retrieval from a Dedicated Multispectral Imaging System Applied to Dermatology/Cosmetology

    PubMed Central

    2013-01-01

    In vivo quantitative assessment of skin lesions is an important step in the evaluation of skin condition. An objective measurement device can help as a valuable tool for skin analysis. We propose an explorative new multispectral camera specifically developed for dermatology/cosmetology applications. The multispectral imaging system provides images of skin reflectance at different wavebands covering visible and near-infrared domain. It is coupled with a neural network-based algorithm for the reconstruction of reflectance cube of cutaneous data. This cube contains only skin optical reflectance spectrum in each pixel of the bidimensional spatial information. The reflectance cube is analyzed by an algorithm based on a Kubelka-Munk model combined with evolutionary algorithm. The technique allows quantitative measure of cutaneous tissue and retrieves five skin parameter maps: melanin concentration, epidermis/dermis thickness, haemoglobin concentration, and the oxygenated hemoglobin. The results retrieved on healthy participants by the algorithm are in good accordance with the data from the literature. The usefulness of the developed technique was proved during two experiments: a clinical study based on vitiligo and melasma skin lesions and a skin oxygenation experiment (induced ischemia) with healthy participant where normal tissues are recorded at normal state and when temporary ischemia is induced. PMID:24159326

  3. 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.

  4. Liquid water path retrieval using the lowest frequency channels of Fengyun-3C Microwave Radiation Imager (MWRI)

    NASA Astrophysics Data System (ADS)

    Tang, Fei; Zou, Xiaolei

    2017-12-01

    The Microwave Radiation Imager (MWRI) on board Chinese Fengyun-3 (FY-3) satellites provides measurements at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with both horizontal and vertical polarization channels. Brightness temperature measurements of those channels with their central frequencies higher than 19 GHz from satellite-based microwave imager radiometers had traditionally been used to retrieve cloud liquid water path (LWP) over ocean. The results show that the lowest frequency channels are the most appropriate for retrieving LWP when its values are large. Therefore, a modified LWP retrieval algorithm is developed for retrieving LWP of different magnitudes involving not only the high frequency channels but also the lowest frequency channels of FY-3 MWRI. The theoretical estimates of the LWP retrieval errors are between 0.11 and 0.06 mm for 10.65- and 18.7-GHz channels and between 0.02 and 0.04 mm for 36.5- and 89.0-GHz channels. It is also shown that the brightness temperature observations at 10.65 GHz can be utilized to better retrieve the LWP greater than 3 mm in the eyewall region of Super Typhoon Neoguri (2014). The spiral structure of clouds within and around Typhoon Neoguri can be well captured by combining the LWP retrievals from different frequency channels.

  5. Model-based VQ for image data archival, retrieval and distribution

    NASA Technical Reports Server (NTRS)

    Manohar, Mareboyana; Tilton, James C.

    1995-01-01

    An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

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

    NASA Astrophysics Data System (ADS)

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

    2017-06-01

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

  7. Personal Photo Enhancement Using Internet Photo Collections.

    PubMed

    Zhang, Chenxi; Gao, Jizhou; Wang, Oliver; Georgel, Pierre; Yang, Ruigang; Davis, James; Frahm, Jan-Michael; Pollefeys, Marc

    2013-04-26

    Given the growth of Internet photo collections we now have a visual index of all major cities and tourist sites in the world. However, it is still a difficult task to capture that perfect shot with your own camera when visiting these places, especially when your camera itself has limitations, such as a limited field of view. In this paper, we propose a framework to overcome the imperfections of personal photos of tourist sites using the rich information provided by large scale Internet photo collections. Our method deploys state-of-the-art techniques for constructing initial 3D models from photo collections. The same techniques are then used to register personal photos to these models, allowing us to augment personal 2D images with 3D information. This strong available scene prior allows us to address a number of traditionally challenging image enhancement techniques, and achieve high quality results using simple and robust algorithms. Specifically, we demonstrate automatic foreground segmentation, mono-to-stereo conversion, the field of view expansion, photometric enhancement, and additionally automatic annotation with geo-location and tags. Our method clearly demonstrates some possible benefits of employing the rich information contained in on-line photo databases to efficiently enhance and augment one’s own personal photos.

  8. Towards case-based medical learning in radiological decision making using content-based image retrieval.

    PubMed

    Welter, Petra; Deserno, Thomas M; Fischer, Benedikt; Günther, Rolf W; Spreckelsen, Cord

    2011-10-27

    Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. The IBCR-RE paradigm incorporates a novel combination of essential aspects

  9. Validation of Rain Rate Retrievals for the Airborne Hurricane Imaging Radiometer (HIRAD)

    NASA Technical Reports Server (NTRS)

    Jacob, Maria Marta; Salemirad, Matin; Jones, W. Linwood; Biswas, Sayak; Cecil, Daniel

    2015-01-01

    The NASA Hurricane and Severe Storm Sentinel (HS3) mission is an aircraft field measurements program using NASA's unmanned Global Hawk aircraft system for remote sensing and in situ observations of Atlantic and Caribbean Sea hurricanes. One of the principal microwave instruments is the Hurricane Imaging Radiometer (HIRAD), which measures surface wind speeds and rain rates. For validation of the HIRAD wind speed measurement in hurricanes, there exists a comprehensive set of comparisons with the Stepped Frequency Microwave Radiometer (SFMR) with in situ GPS dropwindsondes [1]. However, for rain rate measurements, there are only indirect correlations with rain imagery from other HS3 remote sensors (e.g., the dual-frequency Ka- & Ku-band doppler radar, HIWRAP), which is only qualitative in nature. However, this paper presents results from an unplanned rain rate measurement validation opportunity that occurred in 2013, when HIRAD flew over an intense tropical squall line that was simultaneously observed by the Tampa NEXRAD meteorological radar (Fig. 1). During this experiment, Global Hawk flying at an altitude of 18 km made 3 passes over the rapidly propagating thunderstorm, while the TAMPA NEXRAD perform volume scans on a 5-minute interval. Using the well-documented NEXRAD Z-R relationship, 2D images of rain rate (mm/hr) were obtained at two altitudes (3 km & 6 km), which serve as surface truth for the HIRAD rain rate retrievals. A preliminary comparison of HIRAD rain rate retrievals (image) for the first pass and the corresponding closest NEXRAD rain image is presented in Fig. 2 & 3. This paper describes the HIRAD instrument, which 1D synthetic-aperture thinned array radiometer (STAR) developed by NASA Marshall Space Flight Center [2]. The rain rate retrieval algorithm, developed by Amarin et al. [3], is based on the maximum likelihood estimation (MLE) technique, which compares the observed Tb's at the HIRAD operating frequencies of 4, 5, 6 and 6.6 GHz with

  10. Towards case-based medical learning in radiological decision making using content-based image retrieval

    PubMed Central

    2011-01-01

    Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a

  11. Solar process water heat for the IRIS images custom color photo lab

    NASA Technical Reports Server (NTRS)

    1980-01-01

    The solar facility located at a custom photo laboratory in Mill Valley, California is described. It was designed to provide 59 percent of the hot water requirements for developing photographic film and domestic hot water use. The design load is to provide 6 gallons of hot water per minute for 8 hours per working day at 100 F. It has 640 square feet of flat plate collectors and 360 gallons of hot water storage. The auxillary back up system is a conventional gas-fired water heater. Site and building description, subsystem description, as-built drawings, cost breakdown and analysis, performance analysis, lessons learned, and the operation and maintenance manual are presented.

  12. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Central Library NOAA Privacy Policy | NOAA Disclaimer Last Updated: November 10, 2017

  13. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image ' Waterspouts" by Joseph H. Golden, NOAA Technical Memorandum ERL NSSL-70, 1974. Library Call Number

  14. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image the late Dr. Benjamin Franklin ....", 1806. Volume II, p. 26. Library Call Number PS745 .A2 1806

  15. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Library NOAA Privacy Policy | NOAA Disclaimer Last Updated: November 10, 2017

  16. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image Commerce, National Oceanic & Atmospheric Adminstration (NOAA), NOAA Central Library NOAA Privacy Policy

  17. Mars Hand Lens Imager Sends Ultra High-Res Photo from Mars

    NASA Image and Video Library

    2013-10-17

    This image of a U.S. penny on a calibration target was taken by the Mars Hand Lens Imager MAHLI aboard NASA Curiosity rover in Gale Crater on Mars. At 14 micrometers per pixel, this is the highest-resolution image that MAHLI can acquire.

  18. Effectiveness of Global Features for Automatic Medical Image Classification and Retrieval – the experiences of OHSU at ImageCLEFmed

    PubMed Central

    Kalpathy-Cramer, Jayashree; Hersh, William

    2008-01-01

    In 2006 and 2007, Oregon Health & Science University (OHSU) participated in the automatic image annotation task for medical images at ImageCLEF, an annual international benchmarking event that is part of the Cross Language Evaluation Forum (CLEF). The goal of the automatic annotation task was to classify 1000 test images based on the Image Retrieval in Medical Applications (IRMA) code, given a set of 10,000 training images. There were 116 distinct classes in 2006 and 2007. We evaluated the efficacy of a variety of primarily global features for this classification task. These included features based on histograms, gray level correlation matrices and the gist technique. A multitude of classifiers including k-nearest neighbors, two-level neural networks, support vector machines, and maximum likelihood classifiers were evaluated. Our official error rates for the 1000 test images were 26% in 2006 using the flat classification structure. The error count in 2007 was 67.8 using the hierarchical classification error computation based on the IRMA code in 2007. Confusion matrices as well as clustering experiments were used to identify visually similar classes. The use of the IRMA code did not help us in the classification task as the semantic hierarchy of the IRMA classes did not correspond well with the hierarchy based on clustering of image features that we used. Our most frequent misclassification errors were along the view axis. Subsequent experiments based on a two-stage classification system decreased our error rate to 19.8% for the 2006 dataset and our error count to 55.4 for the 2007 data. PMID:19884953

  19. Plasmonic fluorescent CdSe/Cu2S hybrid nanocrystals for multichannel imaging and cancer directed photo-thermal therapy

    NASA Astrophysics Data System (ADS)

    Sheikh Mohamed, M.; Poulose, Aby Cheruvathoor; Veeranarayanan, Srivani; Romero Aburto, Rebecca; Mitcham, Trevor; Suzuki, Yuko; Sakamoto, Yasushi; Ajayan, Pulickel M.; Bouchard, Richard R.; Yoshida, Yasuhiko; Maekawa, Toru; Sakthi Kumar, D.

    2016-04-01

    A simple, crude Jatropha curcas (JC) oil-based synthesis approach, devoid of any toxic phosphine and pyrophoric ligands, to produce size and shape tuned CdSe QDs and a further copper sulfide (Cu2S) encasing is presented. The QDs exhibited excellent photoluminescent properties with narrow band gap emission. Furthermore, the Cu2S shell rendered additional cytocompatibility and stability to the hybrid nanomaterial, which are major factors for translational and clinical applications of QDs. The nanocomposites were PEGylated and folate conjugated to augment their cytoamiability and enhance their specificity towards cancer cells. The nanohybrids possess potentials for visible, near infrared (NIR), photoacoustic (PA) and computed tomography (μCT) imaging. The diverse functionality of the composite was derived from the multi-channel imaging abilities and thermal competence on NIR laser irradiation to specifically actuate the photo-thermal ablation of brain cancer cells.A simple, crude Jatropha curcas (JC) oil-based synthesis approach, devoid of any toxic phosphine and pyrophoric ligands, to produce size and shape tuned CdSe QDs and a further copper sulfide (Cu2S) encasing is presented. The QDs exhibited excellent photoluminescent properties with narrow band gap emission. Furthermore, the Cu2S shell rendered additional cytocompatibility and stability to the hybrid nanomaterial, which are major factors for translational and clinical applications of QDs. The nanocomposites were PEGylated and folate conjugated to augment their cytoamiability and enhance their specificity towards cancer cells. The nanohybrids possess potentials for visible, near infrared (NIR), photoacoustic (PA) and computed tomography (μCT) imaging. The diverse functionality of the composite was derived from the multi-channel imaging abilities and thermal competence on NIR laser irradiation to specifically actuate the photo-thermal ablation of brain cancer cells. Electronic supplementary information (ESI

  20. A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

    PubMed

    Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

    2007-01-01

    A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

  1. Bone age assessment by content-based image retrieval and case-based reasoning

    NASA Astrophysics Data System (ADS)

    Fischer, Benedikt; Welter, Petra; Grouls, Christoph; Günther, Rolf W.; Deserno, Thomas M.

    2011-03-01

    Skeletal maturity is assessed visually by comparing hand radiographs to a standardized reference image atlas. Most common are the methods by Greulich & Pyle and Tanner & Whitehouse. For computer-aided diagnosis (CAD), local image regions of interest (ROI) such as the epiphysis or the carpal areas are extracted and evaluated. Heuristic approaches trying to automatically extract, measure and classify bones and distances between bones suffer from the high variability of biological material and the differences in bone development resulting from age, gender and ethnic origin. Content-based image retrieval (CBIR) provides a robust solution without delineating and measuring bones. In this work, epiphyseal ROIs (eROIS) of a hand radiograph are compared to previous cases with known age, mimicking a human observer. Leaving-one-out experiments are conducted on 1,102 left hand radiographs and 15,428 metacarpal and phalangeal eROIs from the publicly available USC hand atlas. The similarity of the eROIs is assessed by a combination of cross-correlation, image distortion model, and Tamura texture features, yielding a mean error rate of 0.97 years and a variance of below 0.63 years. Furthermore, we introduce a publicly available online-demonstration system, where queries on the USC dataset as well as on uploaded radiographs are performed for instant CAD. In future, we plan to evaluate physician with CBIR-CAD against physician without CBIR-CAD rather than physician vs. CBIR-CAD.

  2. How does signal fade on photo-stimulable storage phosphor imaging plates when scanned with a delay and what is the effect on image quality?

    PubMed

    Ang, Dan B; Angelopoulos, Christos; Katz, Jerald O

    2006-11-01

    The goals of this in vitro study were to determine the effect of signal fading of DenOptix photo-stimulable storage phosphor imaging plates scanned with a delay and to determine the effect on the diagnostic quality of the image. In addition, we sought to correlate signal fading with image spatial resolution and average pixel intensity values. Forty-eight images were obtained of a test specimen apparatus and scanned at 6 delayed time intervals: immediately scanned, 1 hour, 8 hours, 24 hours, 72 hours, and 168 hours. Six general dentists using Vixwin2000 software performed a measuring task to determine the location of an endodontic file tip and root apex. One-way ANOVA with repeated measures was used to determine the effect of signal fading (delayed scan time) on diagnostic image quality and average pixel intensity value. There was no statistically significant difference in diagnostic image quality resulting from signal fading. No difference was observed in spatial resolution of the images. There was a statistically significant difference in the pixel intensity analysis of an 8-step aluminum wedge between immediate scanning and 24-hour delayed scan time. There was an effect of delayed scanning on the average pixel intensity value. However, there was no effect on image quality and raters' ability to perform a clinical identification task. Proprietary software of the DenOptix digital imaging system demonstrates an excellent ability to process a delayed scan time signal and create an image of diagnostic quality.

  3. Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

    PubMed

    Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

    Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

  4. Hib Photos

    MedlinePlus

    ... fluid culture positive for Haemophilus influenzae , type b (Gram stain) www.vaccineinformation.org/photos/hib_aap001.jpg Copyright American Academy of Pediatrics Haemophilus influenzae type b. ... gram-negative Haemophilus influenzae bacteria www.vaccineinformation.org/photos/ ...

  5. Data Retrieval Algorithms for Validating the Optical Transient Detector and the Lightning Imaging Sensor

    NASA Technical Reports Server (NTRS)

    Koshak, W. J.; Blakeslee, R. J.; Bailey, J. C.

    2000-01-01

    A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions. Solutions for the plane (i.e., no earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated datasets, and the relative influence of bearing and arrival time data an the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA:s Optical Transient Detector and Lightning Imaging Sensor. A quadratic planar solution that is useful when only three arrival time measurements are available is also introduced. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in sc)iirce location, Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated datasets, and the results are generally better than those obtained from the three-station linear planar method when bearing errors are about 2 deg.

  6. Learning binary code via PCA of angle projection for image retrieval

    NASA Astrophysics Data System (ADS)

    Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

    2018-01-01

    With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  8. Retrieving Atmospheric Dust Loading on Mars Using Engineering Cameras and MSL's Mars Hand Lens Imager (MAHLI)

    NASA Astrophysics Data System (ADS)

    Wolfe, C. A.; Lemmon, M. T.

    2015-12-01

    Dust in the Martian atmosphere influences energy deposition, dynamics, and the viability of solar powered exploration vehicles. The Viking, Pathfinder, Spirit, Opportunity, Phoenix, and Curiosity landers and rovers each included the ability to image the Sun with a science camera equipped with a neutral density filter. Direct images of the Sun not only provide the ability to measure extinction by dust and ice in the atmosphere, but also provide a variety of constraints on the Martian dust and water cycles. These observations have been used to characterize dust storms, to provide ground truth sites for orbiter-based global measurements of dust loading, and to help monitor solar panel performance. In the cost-constrained environment of Mars exploration, future missions may omit such cameras, as the solar-powered InSight mission has. We seek to provide a robust capability of determining atmospheric opacity from sky images taken with cameras that have not been designed for solar imaging, such as the engineering cameras onboard Opportunity and the Mars Hand Lens Imager (MAHLI) on Curiosity. Our investigation focuses primarily on the accuracy of a method that determines optical depth values using scattering models that implement the ratio of sky radiance measurements at different elevation angles, but at the same scattering angle. Operational use requires the ability to retrieve optical depth on a timescale useful to mission planning, and with an accuracy and precision sufficient to support both mission planning and validating orbital measurements. We will present a simulation-based assessment of imaging strategies and their error budgets, as well as a validation based on the comparison of direct extinction measurements from archival Navcam, Hazcam, and MAHLI camera data.

  9. Photo-Acoustic Ultrasound Imaging to Distinguish Benign from Malignant Prostate Cancer

    DTIC Science & Technology

    2016-09-01

    from the inside out. Ultrasound imaging provides a basic view of the structure of the prostate while photoacoustic contrast is predicted to enhance...University Page 2 of 13 1. INTRODUCTION: Ultrasound imaging uses sound waves at frequencies above the human hearing range to image organs within the body...An ultrasound transducer delivers a pulse of acoustic energy into the area of interest and listens for the echoes which return as the sound waves

  10. Rotation-robust math symbol recognition and retrieval using outer contours and image subsampling

    NASA Astrophysics Data System (ADS)

    Zhu, Siyu; Hu, Lei; Zanibbi, Richard

    2013-01-01

    This paper presents an unified recognition and retrieval system for isolated offline printed mathematical symbols for the first time. The system is based on nearest neighbor scheme and uses modified Turning Function and Grid Features to calculate the distance between two symbols based on Sum of Squared Difference. An unwrap process and an alignment process are applied to modify Turning Function to deal with the horizontal and vertical shift caused by the changing of staring point and rotation. This modified Turning Function make our system robust against rotation of the symbol image. The system obtains top-1 recognition rate of 96.90% and 47.27% Area Under Curve (AUC) of precision/recall plot on the InftyCDB-3 dataset. Experiment result shows that the system with modified Turning Function performs significantly better than the system with original Turning Function on the rotated InftyCDB-3 dataset.

  11. Single shot multi-wavelength phase retrieval with coherent modulation imaging.

    PubMed

    Dong, Xue; Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang

    2018-04-15

    A single shot multi-wavelength phase retrieval method is proposed by combining common coherent modulation imaging (CMI) and a low rank mixed-state algorithm together. A radiation beam consisting of multi-wavelength is illuminated on the sample to be observed, and the exiting field is incident on a random phase plate to form speckle patterns, which is the incoherent superposition of diffraction patterns of each wavelength. The exiting complex amplitude of the sample including both the modulus and phase of each wavelength can be reconstructed simultaneously from the recorded diffraction intensity using a low rank mixed-state algorithm. The feasibility of this proposed method was verified with visible light experimentally. This proposed method not only makes CMI realizable with partially coherent illumination but also can extend its application to various traditionally unrelated fields, where several wavelengths should be considered simultaneously.

  12. First Results of AirMSPI Imaging Polarimetry at ORACLES 2016: Aerosol and Water Cloud Retrievals

    NASA Astrophysics Data System (ADS)

    van Harten, G.; Xu, F.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Jovanovic, V. M.; Cairns, B.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

    2017-12-01

    The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) is a remote sensing instrument for the characterization of atmospheric aerosols and clouds. We will report on the successful deployment and resulting data products of AirMSPI in the 2016 field campaign as part of NASA's ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES). The goal of this five-year investigation is to study the impacts of African biomass burning aerosols on the radiative properties of the subtropical stratocumulus cloud deck over the southeast Atlantic Ocean. On board the NASA ER-2 high-altitude aircraft, AirMSPI collected over 4000 high-resolution images on 16 days. The observations are performed in two different modes: step-and-stare mode, in which a 10x10 km target is observed from 9 view angles at 10 m resolution, and sweep mode, where a 80-100 km along-track by 10-25 km across-track target is observed with continuously changing view angle between ±67° at 25 m resolution. This Level 1B2 calibrated and georectified imagery is publically available at the NASA Langley Atmospheric Science Data Center (ASDC)*. We will then describe the Level 2 water cloud products that will be made publically available, viz. optical depth and droplet size distribution, which are retrieved using a polarimetric algorithm. Finally, we will present the results of a recently developed research algorithm for the simultaneous retrieval of these cloud properties and above-cloud aerosols, and validations using collocated High Spectral Resolution Lidar-2 (HSRL-2) and Research Scanning Polarimeter (RSP) products. * https://eosweb.larc.nasa.gov/project/airmspi/airmspi_table

  13. Speed of Dog Adoption: Impact of Online Photo Traits.

    PubMed

    Lampe, Rachel; Witte, Thomas H

    2015-01-01

    The Internet has radically changed how dogs are advertised for adoption in the United States. This study was used to investigate how different characteristics in dogs' photos presented online affected the speed of their adoptions, as a proof of concept to encourage more research in this field. The study analyzed the 1st images of 468 adopted young and adult black dogs identified as Labrador Retriever mixed breeds across the United States. A subjective global measure of photo quality had the largest impact on time to adoption. Other photo traits that positively impacted adoption speed included direct canine eye contact with the camera, the dog standing up, the photo being appropriately sized, an outdoor photo location, and a nonblurry image. Photos taken in a cage, dogs wearing a bandana, dogs having a visible tongue, and some other traits had no effect on how fast the dogs were adopted. Improving the quality of online photos of dogs presented for adoption may speed up and possibly increase the number of adoptions, thereby providing a cheap and easy way to help fight the homeless companion animal population problem.

  14. Inflight calibration of the modular airborne imaging spectrometer (MAIS) and its application to reflectance retrieval

    NASA Astrophysics Data System (ADS)

    Min, Xiangjun; Zhu, Yonghao

    1998-08-01

    Inflight experiment of Modular Airborne Imaging Spectrometer (MAIS) and ground-based measurements using GER MARK-V spectroradiometer simultaneously with the MAIS overpass were performed during Autumn 1995 at the semiarid area of Inner Mongolia, China. Based on these measurements and MAIS image data, we designed a method for the radiometric calibration of MAIS sensor using 6S and LOWTRAN 7 codes. The results show that the uncertainty of MAIS calibration is about 8% in the visible and near infrared wavelengths (0.4 - 1.2 micrometer). To verify our calibration algorithm, the calibrated results of MAIS sensor was used to derive the ground reflectances. The accuracy of reflectance retrieval is about 8.5% in the spectral range of 0.4 to 1.2 micrometer, i.e., the uncertainty of derived near-nadir reflectances is within 0.01 - 0.05 in reflectance unit at ground reflectance between 3% and 50%. The distinguishing feature of the ground-based measurements, which will be paid special attention in this paper, is that obtaining simultaneously the reflectance factors of the calibration target, atmospheric optical depth, and water vapor abundance from the same one set of measurement data by only one suit of instruments. The analysis indicates that the method presented here is suitable to the quantitative analysis of imaging spectral data in China.

  15. Photo-multiplier Tube Based Hybrid MRI and Frequency Domain Fluorescence Tomography System for Small Animal Imaging

    PubMed Central

    Lin, Y; Ghijsen, M T; Gao, H; Liu, N; Nalcioglu, O; Gulsen, G

    2014-01-01

    Fluorescence tomography (FT) is a promising molecular imaging technique that can spatially resolve both fluorophore concentration and lifetime parameters. However, recovered fluorophore parameters highly depend on the size and depth of the object due to the ill-posedness of the FT inverse problem. Structural a priori information from another high spatial resolution imaging modality has been demonstrated to significantly improve FT reconstruction accuracy. In this study, we have constructed a combined magnetic resonance imaging (MRI) and FT system for small animal imaging. A photo-multiplier tube (PMT) is used as the detector to acquire frequency domain FT measurements. This is the first MR-compatible time-resolved FT system that can reconstruct both fluorescence concentration and lifetime maps simultaneously. The performance of the hybrid system is evaluated with phantom studies. Two different fluorophores, Indocyanine Green (ICG) and 3-3′ Diethylthiatricarbocyanine Iodide (DTTCI), which have similar excitation and emission spectra but different lifetimes, are utilized. The fluorescence concentration and lifetime maps are both reconstructed with and without the structural a priori information obtained from MRI for comparison. We show that the hybrid system can accurately recover both fluorescence intensity and lifetime within 10% error for two 4.2 mm-diameter cylindrical objects embedded in a 38 mm-diameter cylindrical phantom when MRI structural a priori information is utilized. PMID:21753235

  16. Computer-aided diagnostics of screening mammography using content-based image retrieval

    NASA Astrophysics Data System (ADS)

    Deserno, Thomas M.; Soiron, Michael; de Oliveira, Júlia E. E.; de A. Araújo, Arnaldo

    2012-03-01

    Breast cancer is one of the main causes of death among women in occidental countries. In the last years, screening mammography has been established worldwide for early detection of breast cancer, and computer-aided diagnostics (CAD) is being developed to assist physicians reading mammograms. A promising method for CAD is content-based image retrieval (CBIR). Recently, we have developed a classification scheme of suspicious tissue pattern based on the support vector machine (SVM). In this paper, we continue moving towards automatic CAD of screening mammography. The experiments are based on in total 10,509 radiographs that have been collected from different sources. From this, 3,375 images are provided with one and 430 radiographs with more than one chain code annotation of cancerous regions. In different experiments, this data is divided into 12 and 20 classes, distinguishing between four categories of tissue density, three categories of pathology and in the 20 class problem two categories of different types of lesions. Balancing the number of images in each class yields 233 and 45 images remaining in each of the 12 and 20 classes, respectively. Using a two-dimensional principal component analysis, features are extracted from small patches of 128 x 128 pixels and classified by means of a SVM. Overall, the accuracy of the raw classification was 61.6 % and 52.1 % for the 12 and the 20 class problem, respectively. The confusion matrices are assessed for detailed analysis. Furthermore, an implementation of a SVM-based CBIR system for CADx in screening mammography is presented. In conclusion, with a smarter patch extraction, the CBIR approach might reach precision rates that are helpful for the physicians. This, however, needs more comprehensive evaluation on clinical data.

  17. PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

    NASA Astrophysics Data System (ADS)

    Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

    2004-11-01

    Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

  18. American Alcohol Photo Stimuli (AAPS): A standardized set of alcohol and matched non-alcohol images.

    PubMed

    Stauffer, Christopher S; Dobberteen, Lily; Woolley, Joshua D

    2017-11-01

    Photographic stimuli are commonly used to assess cue reactivity in the research and treatment of alcohol use disorder. The stimuli used are often non-standardized, not properly validated, and poorly controlled. There are no previously published, validated, American-relevant sets of alcohol images created in a standardized fashion. We aimed to: 1) make available a standardized, matched set of photographic alcohol and non-alcohol beverage stimuli, 2) establish face validity, the extent to which the stimuli are subjectively viewed as what they are purported to be, and 3) establish construct validity, the degree to which a test measures what it claims to be measuring. We produced a standardized set of 36 images consisting of American alcohol and non-alcohol beverages matched for basic color, form, and complexity. A total of 178 participants (95 male, 82 female, 1 genderqueer) rated each image for appetitiveness. An arrow-probe task, in which matched pairs were categorized after being presented for 200 ms, assessed face validity. Criteria for construct validity were met if variation in AUDIT scores were associated with variation in performance on tasks during alcohol image presentation. Overall, images were categorized with >90% accuracy. Participants' AUDIT scores correlated significantly with alcohol "want" and "like" ratings [r(176) = 0.27, p = <0.001; r(176) = 0.36, p = <0.001] and arrow-probe latency [r(176) = -0.22, p = 0.004], but not with non-alcohol outcomes. Furthermore, appetitive ratings and arrow-probe latency for alcohol, but not non-alcohol, differed significantly for heavy versus light drinkers. Our image set provides valid and reliable alcohol stimuli for both explicit and implicit tests of cue reactivity. The use of standardized, validated, reliable image sets may improve consistency across research and treatment paradigms.

  19. Encryption of QR code and grayscale image in interference-based scheme with high quality retrieval and silhouette problem removal

    NASA Astrophysics Data System (ADS)

    Qin, Yi; Wang, Hongjuan; Wang, Zhipeng; Gong, Qiong; Wang, Danchen

    2016-09-01

    In optical interference-based encryption (IBE) scheme, the currently available methods have to employ the iterative algorithms in order to encrypt two images and retrieve cross-talk free decrypted images. In this paper, we shall show that this goal can be achieved via an analytical process if one of the two images is QR code. For decryption, the QR code is decrypted in the conventional architecture and the decryption has a noisy appearance. Nevertheless, the robustness of QR code against noise enables the accurate acquisition of its content from the noisy retrieval, as a result of which the primary QR code can be exactly regenerated. Thereafter, a novel optical architecture is proposed to recover the grayscale image by aid of the QR code. In addition, the proposal has totally eliminated the silhouette problem existing in the previous IBE schemes, and its effectiveness and feasibility have been demonstrated by numerical simulations.

  20. Retrieval of suspended sediment concentrations using Landsat-8 OLI satellite images in the Orinoco River (Venezuela)

    NASA Astrophysics Data System (ADS)

    Yepez, Santiago; Laraque, Alain; Martinez, Jean-Michel; De Sa, Jose; Carrera, Juan Manuel; Castellanos, Bartolo; Gallay, Marjorie; Lopez, Jose L.

    2018-01-01

    In this study, 81 Landsat-8 scenes acquired from 2013 to 2015 were used to estimate the suspended sediment concentration (SSC) in the Orinoco River at its main hydrological station at Ciudad Bolivar, Venezuela. This gauging station monitors an upstream area corresponding to 89% of the total catchment area where the mean discharge is of 33,000 m3·s-1. SSC spatial and temporal variabilities were analyzed in relation to the hydrological cycle and to local geomorphological characteristics of the river mainstream. Three types of atmospheric correction models were evaluated to correct the Landsat-8 images: DOS, FLAASH, and L8SR. Surface reflectance was compared with monthly water sampling to calibrate a SSC retrieval model using a bootstrapping resampling. A regression model based on surface reflectance at the Near-Infrared wavelengths showed the best performance: R2 = 0.92 (N = 27) for the whole range of SSC (18 to 203 mg·l-1) measured at this station during the studied period. The method offers a simple new approach to estimate the SSC along the lower Orinoco River and demonstrates the feasibility and reliability of remote sensing images to map the spatiotemporal variability in sediment transport over large rivers.

  1. A spatial data handling system for retrieval of images by unrestricted regions of user interest

    NASA Technical Reports Server (NTRS)

    Dorfman, Erik; Cromp, Robert F.

    1992-01-01

    The Intelligent Data Management (IDM) project at NASA/Goddard Space Flight Center has prototyped an Intelligent Information Fusion System (IIFS), which automatically ingests metadata from remote sensor observations into a large catalog which is directly queryable by end-users. The greatest challenge in the implementation of this catalog was supporting spatially-driven searches, where the user has a possible complex region of interest and wishes to recover those images that overlap all or simply a part of that region. A spatial data management system is described, which is capable of storing and retrieving records of image data regardless of their source. This system was designed and implemented as part of the IIFS catalog. A new data structure, called a hypercylinder, is central to the design. The hypercylinder is specifically tailored for data distributed over the surface of a sphere, such as satellite observations of the Earth or space. Operations on the hypercylinder are regulated by two expert systems. The first governs the ingest of new metadata records, and maintains the efficiency of the data structure as it grows. The second translates, plans, and executes users' spatial queries, performing incremental optimization as partial query results are returned.

  2. A novel class sensitive hashing technique for large-scale content-based remote sensing image retrieval

    NASA Astrophysics Data System (ADS)

    Reato, Thomas; Demir, Begüm; Bruzzone, Lorenzo

    2017-10-01

    This paper presents a novel class sensitive hashing technique in the framework of large-scale content-based remote sensing (RS) image retrieval. The proposed technique aims at representing each image with multi-hash codes, each of which corresponds to a primitive (i.e., land cover class) present in the image. To this end, the proposed method consists of a three-steps algorithm. The first step is devoted to characterize each image by primitive class descriptors. These descriptors are obtained through a supervised approach, which initially extracts the image regions and their descriptors that are then associated with primitives present in the images. This step requires a set of annotated training regions to define primitive classes. A correspondence between the regions of an image and the primitive classes is built based on the probability of each primitive class to be present at each region. All the regions belonging to the specific primitive class with a probability higher than a given threshold are highly representative of that class. Thus, the average value of the descriptors of these regions is used to characterize that primitive. In the second step, the descriptors of primitive classes are transformed into multi-hash codes to represent each image. This is achieved by adapting the kernel-based supervised locality sensitive hashing method to multi-code hashing problems. The first two steps of the proposed technique, unlike the standard hashing methods, allow one to represent each image by a set of primitive class sensitive descriptors and their hash codes. Then, in the last step, the images in the archive that are very similar to a query image are retrieved based on a multi-hash-code-matching scheme. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed technique in terms of retrieval accuracy when compared to the standard hashing methods.

  3. Atmospheric Retrieval Analysis of the Directly Imaged Exoplanet HR 8799b

    NASA Astrophysics Data System (ADS)

    Lee, Jae-Min; Heng, Kevin; Irwin, Patrick G. J.

    2013-12-01

    Directly imaged exoplanets are unexplored laboratories for the application of the spectral and temperature retrieval method, where the chemistry and composition of their atmospheres are inferred from inverse modeling of the available data. As a pilot study, we focus on the extrasolar gas giant HR 8799b, for which more than 50 data points are available. We upgrade our non-linear optimal estimation retrieval method to include a phenomenological model of clouds that requires the cloud optical depth and monodisperse particle size to be specified. Previous studies have focused on forward models with assumed values of the exoplanetary properties; there is no consensus on the best-fit values of the radius, mass, surface gravity, and effective temperature of HR 8799b. We show that cloud-free models produce reasonable fits to the data if the atmosphere is of super-solar metallicity and non-solar elemental abundances. Intermediate cloudy models with moderate values of the cloud optical depth and micron-sized particles provide an equally reasonable fit to the data and require a lower mean molecular weight. We report our best-fit values for the radius, mass, surface gravity, and effective temperature of HR 8799b. The mean molecular weight is about 3.8, while the carbon-to-oxygen ratio is about unity due to the prevalence of carbon monoxide. Our study emphasizes the need for robust claims about the nature of an exoplanetary atmosphere to be based on analyses involving both photometry and spectroscopy and inferred from beyond a few photometric data points, such as are typically reported for hot Jupiters.

  4. A Method to Retrieve Rainfall Rate Over Land from TRMM Microwave Imager Observations

    NASA Technical Reports Server (NTRS)

    Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Lau, William K. M. (Technical Monitor)

    2002-01-01

    Over tropical land regions, rain rate maxima in mesoscale convective systems revealed by the Precipitation Radar (PR) flown on the Tropical Rainfall Measuring Mission (TRMM) satellite are found to correspond to thunderstorms, i.e., Cbs. These Cbs are reflected as minima in the 85 GHz brightness temperature, T85, observed by the TRMM Microwave Imager (TMI) radiometer. Because the magnitude of TMI observations do not discriminate satisfactorily convective and stratiform rain, we developed here a different TMI discrimination method. In this method, two types of Cbs, strong and weak, are inferred from the Laplacian of T85 at minima. Then, to retrieve rain rate, where T85 is less than 270 K, a weak (background) rain rate is deduced using T85 observations. Furthermore, over a circular area of 10 km radius centered at the location of each T85 minimum, an additional Cb component of rain rate is added to the background rain rate. This Cb component of rain rate is estimated with the help of (T19-T37) and T85 observations. Initially, our algorithm is calibrated with the PR rain rate measurements from 20 MCS rain events. After calibration, this method is applied to TMI data taken from several tropical land regions. With the help of the PR observations, we show that the spatial distribution and intensity of rain rate over land estimated from our algorithm are better than those given by the current TMI-Version-5 Algorithm. For this reason, our algorithm may be used to improve the current state of rain retrievals on land.

  5. Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

    NASA Astrophysics Data System (ADS)

    Xu, Feng; van Harten, Gerard; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Bruegge, Carol J.; Dubovik, Oleg

    2017-07-01

    The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high-altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from nine viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov-chain/adding-doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI data sets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI preengineering test flight. The retrieval results including aerosol optical depth, single-scattering albedo, aerosol size and refractive index are compared with Aerosol Robotic Network reference data. We identify the best angular combinations for 2, 3, 5, and 7 angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements and target revisits in constraining aerosol property and surface reflection retrieval.

  6. Organize Your Digital Photos: Display Your Images Without Hogging Hard-Disk Space

    ERIC Educational Resources Information Center

    Branzburg, Jeffrey

    2005-01-01

    According to InfoTrends/CAP Ventures, by the end of this year more than 55 percent of all U.S. households will own at least one digital camera. With so many digital cameras in use, it is important for people to understand how to organize and store digital images in ways that make them easy to find. Additionally, today's affordable, large megapixel…

  7. Scheme for predictive fault diagnosis in photo-voltaic modules using thermal imaging

    NASA Astrophysics Data System (ADS)

    Jaffery, Zainul Abdin; Dubey, Ashwani Kumar; Irshad; Haque, Ahteshamul

    2017-06-01

    Degradation of PV modules can cause excessive overheating which results in a reduced power output and eventually failure of solar panel. To maintain the long term reliability of solar modules and maximize the power output, faults in modules need to be diagnosed at an early stage. This paper provides a comprehensive algorithm for fault diagnosis in solar modules using infrared thermography. Infrared Thermography (IRT) is a reliable, non-destructive, fast and cost effective technique which is widely used to identify where and how faults occurred in an electrical installation. Infrared images were used for condition monitoring of solar modules and fuzzy logic have been used to incorporate intelligent classification of faults. An automatic approach has been suggested for fault detection, classification and analysis. IR images were acquired using an IR camera. To have an estimation of thermal condition of PV module, the faulty panel images were compared to a healthy PV module thermal image. A fuzzy rule-base was used to classify faults automatically. Maintenance actions have been advised based on type of faults.

  8. Avalanche photo diodes in the observatory environment: lucky imaging at 1-2.5 microns

    NASA Astrophysics Data System (ADS)

    Vaccarella, A.; Sharp, R.; Ellis, M.; Singh, S.; Bloxham, G.; Bouchez, A.; Conan, R.; Boz, R.; Bundy, D.; Davies, J.; Espeland, B.; Hart, J.; Herrald, N.; Ireland, M.; Jacoby, G.; Nielsen, J.; Vest, C.; Young, P.; Fordham, B.; Zovaro, A.

    2016-08-01

    The recent availability of large format near-infrared detectors with sub-election readout noise is revolutionizing our approach to wavefront sensing for adaptive optics. However, as with all near-infrared detector technologies, challenges exist in moving from the comfort of the laboratory test-bench into the harsh reality of the observatory environment. As part of the broader adaptive optics program for the GMT, we are developing a near-infrared Lucky Imaging camera for operational deployment at the ANU 2.3 m telescope at Siding Spring Observatory. The system provides an ideal test-bed for the rapidly evolving Selex/SAPHIRA eAPD technology while providing scientific imaging at angular resolution rivalling the Hubble Space Telescope at wavelengths λ = 1.3-2.5 μm.

  9. Photoacoustic diagnosis of burns in rats: two-dimensional photo-acoustic imaging of burned tissue

    NASA Astrophysics Data System (ADS)

    Yamazaki, Mutsuo; Sato, Shunichi; Saito, Daizo; Okada, Yoshiaki; Kurita, Akira; Kikuchi, Makoto; Ashida, Hiroshi; Obara, Minoru

    2003-06-01

    We previously reported that for rat burn models, deep dermal burns and deep burns can be well differentiated by measuring the propagation time of the photoacoustic signals originated from the blood in the healthy skin tissue under the damaged tissue layer. However, the diagnosis was based on point measurement in the wound, and therefore site-dependent information on the injuries was not obtained; such information is very important for diagnosis of extended burns. In the present study, we scanned a photoacoustic detector on the wound and constructed two-dimensional (2-D) images of the blood-originated photoacoustic signals for superficial dermal burns (SDB), deep dermal burns (DDB), deep burns (DB), and healthy skins (control) in rats. For each burn model, site-dependent variation of the signal was observed; the variation probably reflects the distribution of blood vessels in the skin tissue. In spite of the variation, clear differentiation was obtained between SDB, DDB, and DB from the 2D images. The images were constructed as a function of post burn time. Temporal signal variation will be also presented.

  10. Retrieval of the thickness of undeformed sea ice from simulated C-band compact polarimetric SAR images

    NASA Astrophysics Data System (ADS)

    Zhang, Xi; Dierking, Wolfgang; Zhang, Jie; Meng, Junmin; Lang, Haitao

    2016-07-01

    In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric (CP) synthetic aperture radar (SAR) images. The parameter is denoted as the "CP ratio". In model simulations we investigated the sensitivity of the CP ratio to the dielectric constant, ice thickness, ice surface roughness, and radar incidence angle. From the results of the simulations we deduced optimal sea ice conditions and radar incidence angles for the ice thickness retrieval. C-band SAR data acquired over the Labrador Sea in circular transmit and linear receive (CTLR) mode were generated from RADARSAT-2 quad-polarization images. In comparison with results from helicopter-borne measurements, we tested different empirical equations for the retrieval of ice thickness. An exponential fit between the CP ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region, we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.94 for the retrieval procedure when applying it to level ice between 0.1 and 0.8 m thick.

  11. 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.

  12. The spatially resolved characterisation of Egyptian blue, Han blue and Han purple by photo-induced luminescence digital imaging.

    PubMed

    Verri, G

    2009-06-01

    The photo-induced luminescence properties of Egyptian blue, Han blue and Han purple were investigated by means of near-infrared digital imaging. These pigments emit infrared radiation when excited in the visible range. The emission can be recorded by means of a modified commercial digital camera equipped with suitable glass filters. A variety of visible light sources were investigated to test their ability to excite luminescence in the pigments. Light-emitting diodes, which do not emit stray infrared radiation, proved an excellent source for the excitation of luminescence in all three compounds. In general, the use of visible radiation emitters with low emission in the infrared range allowed the presence of the pigments to be determined and their distribution to be spatially resolved. This qualitative imaging technique can be easily applied in situ for a rapid characterisation of materials. The results were compared to those for Egyptian green and for historical and modern blue pigments. Examples of the application of the technique on polychrome works of art are presented.

  13. A Fast Smoothing Algorithm for Post-Processing of Surface Reflectance Spectra Retrieved from Airborne Imaging Spectrometer Data

    PubMed Central

    Gao, Bo-Cai; Liu, Ming

    2013-01-01

    Surface reflectance spectra retrieved from remotely sensed hyperspectral imaging data using radiative transfer models often contain residual atmospheric absorption and scattering effects. The reflectance spectra may also contain minor artifacts due to errors in radiometric and spectral calibrations. We have developed a fast smoothing technique for post-processing of retrieved surface reflectance spectra. In the present spectral smoothing technique, model-derived reflectance spectra are first fit using moving filters derived with a cubic spline smoothing algorithm. A common gain curve, which contains minor artifacts in the model-derived reflectance spectra, is then derived. This gain curve is finally applied to all of the reflectance spectra in a scene to obtain the spectrally smoothed surface reflectance spectra. Results from analysis of hyperspectral imaging data collected with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data are given. Comparisons between the smoothed spectra and those derived with the empirical line method are also presented. PMID:24129022

  14. Simultaneous 3D coincidence imaging of cationic, anionic, and neutral photo-fragments

    NASA Astrophysics Data System (ADS)

    Shahi, Abhishek; Albeck, Yishai; Strasser, Daniel

    2018-01-01

    We present the design and simulations of a 3D coincidence imaging spectrometer for fast beam photofragmentation experiments. Coincidence detection of cationic, neutral, and anionic fragments involves spectrometer aberrations that are successfully corrected by an analytical model combined with exact numerical simulations. The spectrometer performance is experimentally demonstrated by characterization of four different channels of intense 800 nm pulse interaction with F2-: F- + F photodissociation, F + F dissociative photodetachment, F+ + F dissociative ionization, and F+ + F+ coulomb explosion. Improved measurement of F2- photodissociation with a 400 nm photon allows a better determination of the F2- anion dissociation energy, 1.256 ± 0.005 eV.

  15. High-resolution fluorescence imaging for red and far-red SIF retrieval at leaf and canopy scales

    NASA Astrophysics Data System (ADS)

    Albert, L.; Alonso, L.; Cushman, K.; Kellner, J. R.

    2017-12-01

    New commercial-off-the-shelf imaging spectrometers promise the combination of high spatial and spectral resolution needed to retrieve solar induced fluorescence (SIF) at multiple wavelengths for individual plants and even individual leaves from low-altitude airborne or ground-based platforms. Data from these instruments could provide insight into the status of the photosynthetic apparatus at scales of space and time not observable from high-altitude and space-based platforms, and could support calibration and validation activities of current and forthcoming space missions to quantify SIF (OCO-2, OCO-3, FLEX, and GEOCARB). High-spectral resolution enables SIF retrieval from regions of strong telluric absorption by molecular oxygen, and also within numerous solar Fraunhofer lines in atmospheric windows not obscured by oxygen or water absorptions. Here we evaluate algorithms for SIF retrieval using a commercial-off-the-shelf diffraction-grating imaging spectrometer with a spectral sampling interval of 0.05 nm and a FWHM < 0.2 nm throughout the 670 - 780 nm range. We demonstrate the tradeoffs between spatial resolution and signal-to-noise ratio using frame stacking and binning, and evaluate the consequences of these tradeoffs for SIF retrieval using three approaches: (1) oxygen-A and B retrieval; (2) retrieval based exclusively on solar Fraunhofer lines outside regions of telluric gas absorption; and (3) a retrieval based on the combination of these approaches. We evaluate the quality of these methods by comparison with coincident SIF spectra of leaves measured using a hand-held field spectrometer and short-pass filters that block incoming light at wavelengths > 650 or 700 nm. These filters enable a direct measurement of SIF emission > 650 or 700 nm that serves as a benchmark against which retrievals from reflectance spectra can be evaluated. We repeated this comparison between leaf-level SIF emission spectra and retrieved SIF emission spectra for leaves treated with

  16. NOAA Photo Library

    Science.gov Websites

    NOAA Photo Library Banner Takes you to the Top Page Takes you to the About this Site page. Takes you to the Contacts page. Takes you to the HELP page. Takes you to the Credits page. Takes you to the Collections page. Takes you to the search page. Takes you to the Links page. NOAA Photo Library Image

  17. Retrieval of Garstang's emission function from all-sky camera images

    NASA Astrophysics Data System (ADS)

    Kocifaj, Miroslav; Solano Lamphar, Héctor Antonio; Kundracik, František

    2015-10-01

    The emission function from ground-based light sources predetermines the skyglow features to a large extent, while most mathematical models that are used to predict the night sky brightness require the information on this function. The radiant intensity distribution on a clear sky is experimentally determined as a function of zenith angle using the theoretical approach published only recently in MNRAS, 439, 3405-3413. We have made the experiments in two localities in Slovakia and Mexico by means of two digital single lens reflex professional cameras operating with different lenses that limit the system's field-of-view to either 180º or 167º. The purpose of using two cameras was to identify variances between two different apertures. Images are taken at different distances from an artificial light source (a city) with intention to determine the ratio of zenith radiance relative to horizontal irradiance. Subsequently, the information on the fraction of the light radiated directly into the upward hemisphere (F) is extracted. The results show that inexpensive devices can properly identify the upward emissions with adequate reliability as long as the clear sky radiance distribution is dominated by a largest ground-based light source. Highly unstable turbidity conditions can also make the parameter F difficult to find or even impossible to retrieve. The measurements at low elevation angles should be avoided due to a potentially parasitic effect of direct light emissions from luminaires surrounding the measuring site.

  18. Retrieving acoustic energy densities and local pressure amplitudes in microfluidics by holographic time-lapse imaging.

    PubMed

    Cacace, Teresa; Bianco, Vittorio; Paturzo, Melania; Memmolo, Pasquale; Vassalli, Massimo; Fraldi, Massimiliano; Mensitieri, Giuseppe; Ferraro, Pietro

    2018-06-26

    The development of techniques able to characterize and map the pressure field is crucial for the widespread use of acoustofluidic devices in biotechnology and lab-on-a-chip platforms. In fact, acoustofluidic devices are powerful tools for driving precise manipulation of microparticles and cells in microfluidics in non-contact modality. Here, we report a full and accurate characterization of the movement of particles subjected to acoustophoresis in a microfluidic environment by holographic imaging. The particle displacement along the direction of the ultrasound wave propagation, coinciding with the optical axis, is observed and investigated. Two resonance frequencies are explored, varying for each the amplitude of the applied signal. The trajectories of individual tracers, accomplished by holographic measurements, are fitted with the theoretical model thus allowing the retrieval of the acoustic energy densities and pressure amplitudes through full holographic analysis. The absence of prior calibration, being independent of the object shape and the possibility of implementing automatic analysis make the use of holography very appealing for applications in devices for biotechnologies.

  19. CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

    NASA Astrophysics Data System (ADS)

    Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

    2004-02-01

    The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

  20. An algorithm for retrieving rock-desertification from multispectral remote sensing images

    NASA Astrophysics Data System (ADS)

    Xia, Xueqi; Tian, Qingjiu; Liao, Yan

    2009-06-01

    Rock-desertification is a typical environmental and ecological problem in Southwest China. As remote sensing is an important means of monitoring spatial variation of rock-desertification, a method is developed for measurement and information retrieval of rock-desertification from multi-spectral high-resolution remote sensing images. MNF transform is applied to 4-band IKONOS multi-spectral remotely sensed data to reduce the number of spectral dimensions to three. In the 3-demension endmembers are extracted and analyzed. It is found that various vegetations group into a line defined as "vegetation line", in which "dark vegetations", such as coniferous forest and broadleaf forest, continuously change to "bright vegetations", such as grasses. It is presumed that is caused by deferent proportion of shadow mixed in leaves or branches in various types of vegetation. Normalized distance between the endmember of rocks and the vegetation line is defined as Geometric Rock-desertification Index (GRI), which was used to scale rock-desertification. The case study with ground truth validation in Puding, Guizhou province showed successes and the advantages of this method.

  1. Content based Image Retrieval based on Different Global and Local Color Histogram Methods: A Survey

    NASA Astrophysics Data System (ADS)

    Suhasini, Pallikonda Sarah; Sri Rama Krishna, K.; Murali Krishna, I. V.

    2017-02-01

    Different global and local color histogram methods for content based image retrieval (CBIR) are investigated in this paper. Color histogram is a widely used descriptor for CBIR. Conventional method of extracting color histogram is global, which misses the spatial content, is less invariant to deformation and viewpoint changes, and results in a very large three dimensional histogram corresponding to the color space used. To address the above deficiencies, different global and local histogram methods are proposed in recent research. Different ways of extracting local histograms to have spatial correspondence, invariant colour histogram to add deformation and viewpoint invariance and fuzzy linking method to reduce the size of the histogram are found in recent papers. The color space and the distance metric used are vital in obtaining color histogram. In this paper the performance of CBIR based on different global and local color histograms in three different color spaces, namely, RGB, HSV, L*a*b* and also with three distance measures Euclidean, Quadratic and Histogram intersection are surveyed, to choose appropriate method for future research.

  2. A new method for fusion, denoising and enhancement of x-ray images retrieved from Talbot-Lau grating interferometry.

    PubMed

    Scholkmann, Felix; Revol, Vincent; Kaufmann, Rolf; Baronowski, Heidrun; Kottler, Christian

    2014-03-21

    This paper introduces a new image denoising, fusion and enhancement framework for combining and optimal visualization of x-ray attenuation contrast (AC), differential phase contrast (DPC) and dark-field contrast (DFC) images retrieved from x-ray Talbot-Lau grating interferometry. The new image fusion framework comprises three steps: (i) denoising each input image (AC, DPC and DFC) through adaptive Wiener filtering, (ii) performing a two-step image fusion process based on the shift-invariant wavelet transform, i.e. first fusing the AC with the DPC image and then fusing the resulting image with the DFC image, and finally (iii) enhancing the fused image to obtain a final image using adaptive histogram equalization, adaptive sharpening and contrast optimization. Application examples are presented for two biological objects (a human tooth and a cherry) and the proposed method is compared to two recently published AC/DPC/DFC image processing techniques. In conclusion, the new framework for the processing of AC, DPC and DFC allows the most relevant features of all three images to be combined in one image while reducing the noise and enhancing adaptively the relevant image features. The newly developed framework may be used in technical and medical applications.

  3. Joint aerosol and water-leaving radiance retrieval from Airborne Multi-angle SpectroPolarimeter Imager

    NASA Astrophysics Data System (ADS)

    Xu, F.; Dubovik, O.; Zhai, P.; Kalashnikova, O. V.; Diner, D. J.

    2015-12-01

    The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) [1] has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI typically acquires observations of a target area at 9 view angles between ±67° off the nadir. Its spectral channels are centered at 355, 380, 445, 470*, 555, 660*, and 865* nm, where the asterisk denotes the polarimetric bands. In order to retrieve information from the AirMSPI observations, we developed a efficient and flexible retrieval code that can jointly retrieve aerosol and water leaving radiance simultaneously. The forward model employs a coupled Markov Chain (MC) [2] and adding/doubling [3] radiative transfer method which is fully linearized and integrated with a multi-patch retrieval algorithm to obtain aerosol and water leaving radiance/Chl-a information. Various constraints are imposed to improve convergence and retrieval stability. We tested the aerosol and water leaving radiance retrievals using the AirMSPI radiance and polarization measurements by comparing to the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration to the values reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California. In addition, the MC-based retrievals of aerosol properties were compared with GRASP ([4-5]) retrievals for selected cases. The MC-based retrieval approach was then used to systematically explore the benefits of AirMSPI's ultraviolet and polarimetric channels, the use of multiple view angles, and constraints provided by inclusion of bio-optical models of the water-leaving radiance. References [1]. D. J. Diner, et al. Atmos. Meas. Tech. 6, 1717 (2013). [2]. F. Xu et al. Opt. Lett. 36, 2083 (2011). [3]. J. E. Hansen and L.D. Travis. Space Sci. Rev. 16, 527 (1974). [4]. O. Dubovik et al. Atmos. Meas. Tech., 4, 975 (2011). [5]. O. Dubovik et al. SPIE: Newsroom, DOI:10.1117/2.1201408.005558 (2014).

  4. Search and retrieval of medical images for improved diagnosis of neurodegenerative diseases

    NASA Astrophysics Data System (ADS)

    Ekin, Ahmet; Jasinschi, Radu; Turan, Erman; Engbers, Rene; van der Grond, Jeroen; van Buchem, Mark A.

    2007-01-01

    In the medical world, the accuracy of diagnosis is mainly affected by either lack of sufficient understanding of some diseases or the inter-, and/or intra-observer variability of the diagnoses. The former requires understanding the progress of diseases at much earlier stages, extraction of important information from ever growing amounts of data, and finally finding correlations with certain features and complications that will illuminate the disease progression. The latter (inter-, and intra- observer variability) is caused by the differences in the experience levels of different medical experts (inter-observer variability) or by mental and physical tiredness of one expert (intra-observer variability). We believe that the use of large databases can help improve the current status of disease understanding and decision making. By comparing large number of patients, some of the otherwise hidden relations can be revealed that results in better understanding, patients with similar complications can be found, the diagnosis and treatment can be compared so that the medical expert can make a better diagnosis. To this effect, this paper introduces a search and retrieval system for brain MR databases and shows that brain iron accumulation shape provides additional information to the shape-insensitive features, such as the total brain iron load, that are commonly used in the clinics. We propose to use Kendall's correlation value to automatically compare various returns to a query. We also describe a fully automated and fast brain MR image analysis system to detect degenerative iron accumulation in brain, as it is the case in Alzheimer's and Parkinson's. The system is composed of several novel image processing algorithms and has been extensively tested in Leiden University Medical Center over so far more than 600 patients.

  5. A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images

    PubMed Central

    Zhong, Xinke; Labed, Jelila; Zhou, Guoqing; Shao, Kun; Li, Zhao-Liang

    2015-01-01

    The surface temperature (ST) of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR) images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE) of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800–1200 cm−1 and a spectral sampling frequency of 0.25 cm−1. We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE) of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product. PMID:26061199

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

    DOE PAGES

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

    2014-12-01

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

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

    SciTech Connect

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

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

  8. An oil film information retrieval method overcoming the influence of sun glitter, based on AISA+ airborne hyper-spectral image

    NASA Astrophysics Data System (ADS)

    Zhan, Yuanzeng; Mao, Tianming; Gong, Fang; Wang, Difeng; Chen, Jianyu

    2010-10-01

    As an effective survey tool for oil spill detection, the airborne hyper-spectral sensor affords the potentiality for retrieving the quantitative information of oil slick which is useful for the cleanup of spilled oil. But many airborne hyper-spectral images are affected by sun glitter which distorts radiance values and spectral ratios used for oil slick detection. In 2005, there's an oil spill event leaking at oil drilling platform in The South China Sea, and an AISA+ airborne hyper-spectral image recorded this event will be selected for studying in this paper, which is affected by sun glitter terribly. Through a spectrum analysis of the oil and water samples, two features -- "spectral rotation" and "a pair of fixed points" can be found in spectral curves between crude oil film and water. Base on these features, an oil film information retrieval method which can overcome the influence of sun glitter is presented. Firstly, the radiance of the image is converted to normal apparent reflectance (NormAR). Then, based on the features of "spectral rotation" (used for distinguishing oil film and water) and "a pair of fixed points" (used for overcoming the effect of sun glitter), NormAR894/NormAR516 is selected as an indicator of oil film. Finally, by using a threshold combined with the technologies of image filter and mathematic morphology, the distribution and relative thickness of oil film are retrieved.

  9. Assessment of capabilities of multiangle imaging photo-polarimetry for atmospheric correction in presence of absorbing aerosols

    NASA Astrophysics Data System (ADS)

    Kalashnikova, O. V.; Garay, M. J.; Xu, F.; Seidel, F. C.; Diner, D. J.

    2015-12-01

    Satellite remote sensing of ocean color is a critical tool for assessing the productivity of marine ecosystems and monitoring changes resulting from climatic or environmental influences. Yet water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Traditional ocean color retrieval algorithms utilize a standard set of aerosol models and the assumption of negligible water-leaving radiance in the near-infrared. Modern improvements have been developed to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean, where ocean fertilization can impact biological productivity at the base of the marine food chain. Even so, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error. In the UV, the problem of UV-enhanced absorption and nonsphericity of certain aerosol types are amplified due to the increased Rayleigh and aerosol optical depth, especially at off-nadir view angles. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of the work to be described is the assessment of the effects of absorbing aerosol properties on water leaving radiance measurement uncertainty by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. The phase matrices for the spherical smoke particles were calculated using a standard

  10. Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors.

    PubMed

    Husain, Syed Sameed; Bober, Miroslaw

    2017-09-01

    Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the

  11. Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images

    PubMed Central

    Sparks, Rachel; Madabhushi, Anant

    2016-01-01

    Content-based image retrieval (CBIR) retrieves database images most similar to the query image by (1) extracting quantitative image descriptors and (2) calculating similarity between database and query image descriptors. Recently, manifold learning (ML) has been used to perform CBIR in a low dimensional representation of the high dimensional image descriptor space to avoid the curse of dimensionality. ML schemes are computationally expensive, requiring an eigenvalue decomposition (EVD) for every new query image to learn its low dimensional representation. We present out-of-sample extrapolation utilizing semi-supervised ML (OSE-SSL) to learn the low dimensional representation without recomputing the EVD for each query image. OSE-SSL incorporates semantic information, partial class label, into a ML scheme such that the low dimensional representation co-localizes semantically similar images. In the context of prostate histopathology, gland morphology is an integral component of the Gleason score which enables discrimination between prostate cancer aggressiveness. Images are represented by shape features extracted from the prostate gland. CBIR with OSE-SSL for prostate histology obtained from 58 patient studies, yielded an area under the precision recall curve (AUPRC) of 0.53 ± 0.03 comparatively a CBIR with Principal Component Analysis (PCA) to learn a low dimensional space yielded an AUPRC of 0.44 ± 0.01. PMID:27264985

  12. Predictors of photo naming: Dutch norms for 327 photos.

    PubMed

    Shao, Zeshu; Stiegert, Julia

    2016-06-01

    In the present study, we report naming latencies and norms for 327 photos of objects in Dutch. We provide norms for eight psycholinguistic variables: age of acquisition, familiarity, imageability, image agreement, objective and subjective visual complexity, word frequency, word length in syllables and letters, and name agreement. Furthermore, multiple regression analyses revealed that the significant predictors of photo-naming latencies were name agreement, word frequency, imageability, and image agreement. The naming latencies, norms, and stimuli are provided as supplemental materials.

  13. An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model

    PubMed Central

    Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

    2018-01-01

    For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques. PMID:29694429

  14. An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model.

    PubMed

    Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

    2018-01-01

    For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques.

  15. A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

    NASA Astrophysics Data System (ADS)

    Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

    2017-04-01

    The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for

  16. Meningococcal Photos

    MedlinePlus

    ... Vaccine Campaign Podcast: Meningitis Immunization for Adolescents Meningitis Sepsis Meningococcal Photos Recommend on Facebook Tweet Share Compartir ... Vaccine Campaign Podcast: Meningitis Immunization for Adolescents Meningitis Sepsis File Formats Help: How do I view different ...

  17. Oil/water nano-emulsion loaded with cobalt ferrite oxide nanocubes for photo-acoustic and magnetic resonance dual imaging in cancer: in vitro and preclinical studies.

    PubMed

    Vecchione, Raffaele; Quagliariello, Vincenzo; Giustetto, Pierangela; Calabria, Dominic; Sathya, Ayyappan; Marotta, Roberto; Profeta, Martina; Nitti, Simone; Silvestri, Niccolò; Pellegrino, Teresa; Iaffaioli, Rosario V; Netti, Paolo Antonio

    2017-01-01

    Dual imaging dramatically improves detection and early diagnosis of cancer. In this work we present an oil in water (O/W) nano-emulsion stabilized with lecithin and loaded with cobalt ferrite oxide (Co 0.5 Fe 2.5 O 4 ) nanocubes for photo-acoustic and magnetic resonance dual imaging. The nanocarrier is responsive in in vitro photo-acoustic and magnetic resonance imaging (MRI) tests. A clear and significant time-dependent accumulation in tumor tissue is shown in in vivo photo-acoustic studies on a murine melanoma xenograft model. The proposed O/W nano-emulsion exhibits also high values of r 2 /r 1 (ranging from 45 to 85, depending on the magnetic field) suggesting a possible use as T 2 weighted image contrast agents. In addition, viability and cellular uptake studies show no significant cytotoxicity on the fibroblast cell line. We also tested the O/W nano-emulsion loaded with curcumin against melanoma cancer cells demonstrating a significant cytotoxicity and thus showing possible therapeutic effects in addition to the in vivo imaging. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

  20. Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.

    PubMed

    Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan

    2017-02-01

    Visual information of similar nodules could assist the budding radiologists in self-learning. This paper presents a content-based image retrieval (CBIR) system for pulmonary nodules, observed in lung CT images. The reported CBIR systems of pulmonary nodules cannot be put into practice as radiologists need to draw the boundary of nodules during query formation and feature database creation. In the proposed retrieval system, the pulmonary nodules are segmented using a semi-automated technique, which requires a seed point on the nodule from the end-user. The involvement of radiologists in feature database creation is also reduced, as only a seed point is expected from radiologists instead of manual delineation of the boundary of the nodules. The performance of the retrieval system depends on the accuracy of the segmentation technique. Several 3D features are explored to improve the performance of the proposed retrieval system. A set of relevant shape and texture features are considered for efficient representation of the nodules in the feature space. The proposed CBIR system is evaluated for three configurations such as configuration-1 (composite rank of malignancy "1","2" as benign and "4","5" as malignant), configuration-2 (composite rank of malignancy "1","2", "3" as benign and "4","5" as malignant), and configuration-3 (composite rank of malignancy "1","2" as benign and "3","4","5" as malignant). Considering top 5 retrieved nodules and Euclidean distance metric, the precision achieved by the proposed method for configuration-1, configuration-2, and configuration-3 are 82.14, 75.91, and 74.27 %, respectively. The performance of the proposed CBIR system is close to the most recent technique, which is dependent on radiologists for manual segmentation of nodules. A computer-aided diagnosis (CAD) system is also developed based on CBIR paradigm. Performance of the proposed CBIR-based CAD system is close to performance of the CAD system using support vector machine.