I2Cnet medical image annotation service.

The South East Asian Medical Information Center (SEAMIC), one of the major projects of the International Medical Foundation of Japan (IMFJ), was created for the purpose of contributing to better health planning in South East Asian countries through the exchange, generation, and utilization of health and medical related information on a multilateral basis. The 11th SEAMIC Workshop on “Multilateral Collaboration on SEAMIC Health Information Activities with Special Reference to Inter-Country Lending System” was held at Bangkok, Thailand from February 6th to 10th, 1984. There were 18 participants from Indonesia, Malaysia, the Philippines, Singapore, Thailand, Japan and W. H. O. Two technical papers were presented and each participating country presented its respective country report. Six panelists discussed about training programmes for medical and health related information personnel. There were 4 sessions to discuss about the development of inter-country lending system. The main agreements and recommendations are as follows: 1) Compilation and publication of the SEAMIC Union List is March 1987. 2) The provision of one additional photocopy machine to each country; Malaysia, Philippines and Thailand, and two more additional machines to Indonesia was recommended. 3) The guideline and procedure of coupon system was admitted by all participating countries. 4) All six SEAMIC countries including Japan submit a listing of doctoral dissertations and conference proceedings published since 1983. 5) All SEAMIC countries agreed to participate in preparation fo the SEAMIC Index Medicus. This work should be completed by 1986. 6) Collection and compilation of library statistics should be done by SEAMIC annually. 7) “User Study” should be set up to know medical librarians' view concerning SEAMIC services.

Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

BI&T Tell me about the Medical Imaging and Technology Alliance. David Fisher The Medical Imaging & Technology Alliance (MITA), a division of the National Electrical Manufacturers Association (NEMA), is the leading organization and collective voice of medical imaging equipment manufacturers, innovators, and product developers. It represents companies whose sales comprise more than 90 percent of the global market for medical imaging technology. The goals of MITA are to: • Increase the awareness and understanding of the value of medical imaging • Achieve efficient and reasonable regulation of medical imaging technologies • Interact with appropriate government agencies on reimbursement and technology assessment policies • Expand the global acceptance of the digital communications standard (DICOM) that allows digital imaging technologies to interact seamlessly • Improve regulatory harmonization of the global market for medical imaging products • Develop and represent industry positions in technical, trade and other issues • Provide market data unique to this industry

During medical picture transmission, the most pressing concern is security. Medical images must be encrypted since they are extremely sensitive. Watermarking, digital fingerprinting/signature, and encoding are some of the available image security techniques. Images and movies, for example, must be highly encrypted and decoded without losing any content information. Medical photos, for example, require extra protection, and protecting medical images is a critical issue when medical images and related patient information are transferred over public networks. This research work proposes a visual encryption strategy to secure medical pictures before being transmitted or stored in the cloud. This technique makes such pictures of unauthorized people unavailable and also maintains confidentiality, a prime safety requirement. The process made use of a pixel shuffling-based encryption technique and a secret key created from the image. In this research, we encrypted the medical image using modified Arnold Map Encryption and generated secret key values. Therefore, the image is encrypted, and henceforth it is decrypted as well. So this work gave us the encrypted image and decrypted image/original image as well. The modified Arnold Map Encryption tries to add more randomness, thus increasing the entropy of the image and thus makes it harder to decrypt. The modified Arnold Map Encryption is also compared to other algorithms such as Hyper Chaotic, Secure Hash Algorithm-13 (SHA-13), Ten Logistic Maps, Bakers Map, HenonMap, Cross Chaos Map, and 2D Logistic Map and shows better results in terms of encryption speed and Number of Pixel Change Rate (NPCR) value.

Guest editorial

A mobile multi-agent image retrieval system with application in mammography is presented. The image retrieval strategy suggested uses the inherent strengths of mobile agents to return the best possible matches from a distributed set of images in digital medical image libraries available on the Internet. The approach proposed is to perform a simulation of the digital library and to study the dynamics of the system from the perspective of parallel processing, intelligent pre-processing and communication.

The World Wide Web has dramatically altered landscape of information seeking in health. The provision of medical information has historically been business of medical librarians, and their principal clientele has been nurses, and allied health professionals, as well as students in those fields. Accordingly, for decades library schools have seen medical library science as an arcane specialty. The Web, however, has democratized access to health information. Searching for health topics online is now most popular consumer activity after use of email. In this paper, I discuss changes in healthcare information use effected by World Wide Web; give examples of integration of medical librarianship into generalist courses in library and information science (LIS) degree programs; and finally discuss challenges of integrating medical specialization into generalist teaching. Introduction Twenty years ago, in last published survey on this topic, Detlefsen and Gal vin found that 41 of 54 American Library Association (ALA)-accredited library and information science (LIS) degree programs offered at least one course in health sciences or biomedical librarianship.2 Despite apparently high regard for medical specialty in these schools, Detlefsen and Galvin were worried by their findings - not by number of courses offered, but by fact that in these 41 schools, only 25% of full-time faculty self-identified as having a health-related specialty. That is: 75% of these 41 programs were relying on adjuncts to teach, adjuncts who were typically working medical librarians. Adjunct numbers have important implications for specialty fields. Detlefsen and Galvin argued that adjuncts who are working practitioners have content expertise, but because of their position in educational institution, are less able to advocate for change and defend their specialty in curriculum. Because adjuncts typically have full-time employment elsewhere, they are subject to their own employers' needs and responsive to their employers' reward systems before those of schools and programs in which they teach. Full-time faculty, conversely, exist by definition to be full-time educators and not practitioners; and as full-time educators, they are rewarded for maintaining a presence on curriculum and admissions committees that influence training of future specialists and availability of future courses. Finally, full-time faculty members are charged with formal student advising. Adjunct faculty can and do have informal mentoring relationships with their students, but this is not typically considered an explicit function of their job. A May, 2006 review of ALA-accredited LIS program Web sites reveals that of 47 programs either fully or conditionally accredited, virtually all had either medical or health information courses listed in their catalogs, offered at least every 2 years. Twenty-three LIS programs (50%) report a total of 39 full-time faculty identifying either medical librarianship or medical informatics as a research interest.3 Although both medical informatics and medical librarianship focus on medical information, two are not synonymous. Medical informatics is generally defined as the rapidly developing scientific field that deals with biomedical information, data, and knowledge as it intersects with information technology.4 It is an extremely interdisciplinary domain, to which library and information science is one of many important contributing fields. However, medical informatics is dominated by clinicians. Membership in American Medical Informatics Association (AMIA) includes physicians, nurses, dentists, biomedical engineers, medical librarians, researchers, scientists, educators, students and other health care professionals.5 This field, with its origins in medicine and computer science, demands a different, although occasionally overlapping, range of information technology competencies and training than does medical librarianship. …

The use of social media among Saudi residents for medicines related information

Medical image indexing and storage is gaining increased importance. Indexing and retrieval of these images efficiently is becomes an essential task. Indexing of medical images using text or numbers is a cumbersome task, difficult to memorize and time consuming. Indexing and Retrieval of images can be done through query by text and query by image which is also known as content based image retrieval (CBIR). Different medical images possess different texture and shape features. This paper presents a novel and hybrid approach of managing a huge medical image database and retrieving a medical image from the database by fusion of shape and texture features. Image is retrieved by comparing the features of query image and images of database. We attach some document information with each medical image such as patient identity, diseases, age, and case history. It can be used for further diagnostic and analysis purpose. Further the proposed algorithm also updates the database automatically if new query is found. MATLAB ® 7.01 and its image processing toolbox have been used to implement the algorithm.

The use of digital techniques for the production, manipulation and storage of images has resulted in the creation of digital image libraries. These libraries often store many thousands of images. While provision of storage media for such large amounts of data has been straightforward, provision of effective searching and retrieval tools has not. Medicine relies heavily on images as a diagnostic tool. The most obvious example is the X-ray, but many other image forms are in everyday use. Advances in technology are affecting the ways medical images are generated, stored and retrieved. The paper describes the work of the Image Coding and Segmentation to Support Variable Rate Transmission Channels and Variable Resolution Platforms (ICoS) research project currently under way in Bristol UK. ICoS is a project of the Mobile Multimedia University research consortium (MMU) between The University of Bristol, The University of the West of England and Hewlett-Packard Research Laboratories Europe. Funding is provided by the Engineering and Physical Sciences Research Council (EPSRC). The aim of the ICoS project is to demonstrate the practical application of computer networking to medical image libraries. Work at the University of the West of England concentrates on user interface and indexing issues. Metadata is used to organise the images, coded using the World Wide Web Consortium (W3C) standard Resource Description Framework (RDF). We are investigating the application of such standards to medical images, one outcome being to implement a metadata-based medical image library. This paper describes the ICoS project in detail and discusses both metadata systems and user interfaces in the context of medical applications.

To effectively utilize information stored in a digital image library, effective image indexing and retrieval techniques are essential. This paper proposes an image indexing and retrieval technique based on the compressed image data using vector quantization (VQ). By harnessing the characteristics of VQ, the proposed technique is able to capture the spatial relationships of pixels when indexing the image. Experimental results illustrate the robustness of the proposed technique and also show that its retrieval performance is higher compared with existing color-based techniques.

Digital medical images are becoming even more widespread and used in a large variety of applications. Such images are often stored in local repositories and need to be transmitted/ received over the network. Therefore, data compression is an essential mechanism to adopt for improving the transmission time, as well as to optimize the required storage space. However, due to the clinical relevance of such data, lossless techniques are almost ever preferred, given that in such context it is not tolerated any loss of data. In this work, starting from the Medical Images Lossless Compression (MILC) algorithm, which enables the efficient coding of three-dimensional medical images achieving results comparable with the other state-of-art algorithms, we propose Parallel MILC, a fully parallelized version of that algorithm, which provides some attractive features with respect to MILC, especially in terms of execution speedup and scalability. In detail, we propose a novel design and implementation for the MILC algorithm, which is able to exploit the power and the capabilities of the parallel computing paradigm. It is important to point out that Parallel MILC can be executed on several heterogeneous device types supporting OpenCL (i.e. CPU, GPU, FPGA, etc.). The preliminary test results show a significant performance speedup of Parallel MILC compared to MILC. Consequently, the novel algorithm we propose provides MILC with strong scalability properties and complete transparency with respect the underlying hardware.

Necessity of establishing a national information network in medicine is beginning to be recognized in Japan.The trend has been more prominent in the United States where the National Library of Medicine's MEDLARS is actually being operated with its satelite centers located in not only various parts of the country but also in England, in Sweden and now in Australia. Herner's design for a medical library and information system, recommended to the Department of Health, Education and Welfare in 1966, was a plan of very large scale but it had many subsystems already in existence to build up the main scheme on them. The basic idea of this plan might be adaptable in planning our national information system but changes will be necessary to make it fit to our situation.In Japan, medical libraries are fairly active in literature providing services but not so in information services. For instance, out of 51 member libraries of the Japan Medical Library Association, only few of them are doing literature search as their regular service. But on the other hand, these 51 member libraries which include all of 46 medical school libraries, with the total of 3,754,808 bound periodical volumes and books, and subscription of 51,453 periodical (5,036 different titles), lent out 626,612 volumes to their areas, and sent to other member libraries 42,831 of their library materials and their photo copies as interlibrary loan in one year from April 1966 to March 1967. The association divides Japan into 9 districts to serve but the members are not divided evenly. In the case of Kanto district, there are 18 member libraries out of all 51 and they have 1,228,331 volumes, or 32.7% of all 3,754,808 volumes.The units which are to be included in the proposed information network in Japan are these, such as, a national center, district centers, specialized centers, data ceters, interlibrary centers, and the units with clearing house function.The national center will have a wholesale dealer's function in handling literature and switching information. District centers are depending on the national center for the supply of literature and processed information, but they are also the central unit in their own districts. Specialized centers collect all the materials in a certain special subject field, analyse their contents and provides an answer to the requested question in the field. Data center will do similar function but they will handle data and not information. For interlibrary centers which we don't have anything of the sort at the moment, will be set up after the model of the New York Medical Library Center.To carry out this plan, establishment of the national center will be the first and the largest problem of all. The Japan Information Center of Science and Technology (JICST) will be the only possible candidate for this though it is a new comer in medical field and it does not have a large enough medical collection nor experience of handling medical information.But the JICST decided to extend there serving fields to include biomedicine and agriculture. The JICST also is negotiating with the National Library of Medicine in Bethesda on setting up a MEDLARS' searching center in it. Therefore, with close cooperation from the Japan Medical Library Association and its member libraries, it can grow into a satisfactory national center. As for the district centers, 10 or 12 of the largest and most active medical school libraries should be selected and strengthened to make them possible to do their role. Specialized centers, data centers and inter library centers are the ones which should be built up from nothing. An inter library center will be necessary in each of the east and west Japan areas. The national referral center and an information center on “who's doing what research in medicine” should be established in the national center but with help in gathering the needed information for the service from the member libraries of the Japan Medical Library Association. The weak points of the plan are:The necessity of organizing a national network of medical information handling is not fully recognized by researchers, clinicians, and faculty members of the medical schools.There is no medical information system of any size which can be a core or a subsystem of the network, except the Japan Medical Library Association's interlibrary loan system.

Com o advento dos equipamentos digitais de diagnóstico médico, houve uma diminuição do uso de filmes emradiologia. Em contrapartida, o gerenciamento de imagens médicas (IMs) digitalizadas tornou-se uma tarefa crítica. Neste trabalho, apresentamos um protótipo, com base em tecnologias worldwide web (www), que realiza essa função. Ele contempla um servidor de IMs que possibilita a pesquisa e a recuperação dessas imagens armazenadas como arquivos digital imaging and communications in medicine (Dicom), além de receber requisições de serviços de equipamento sem aplicações compatíveis com esse padrão. As IMs podem ser visualizadas e manipuladas dentro de um navegador web (o cliente da aplicação) por meio de uma aplicação Java (applet). Tal abordagem oferece algumas vantagens em relação aos tradicionais sistemas de arquivamento e comunicação de imagens (picture archiving and communication systems [Pacs]), entre as quais a independência de plataformas e facilidade de instalação e de manutenção, a distribuição de dados e a integração com outros sistemas, dentro ou fora da instituição. Basta que se utilize a implementação de políticas de segurança. A simplicidade e a flexibilidade das tecnologias web viabilizam o uso dessa aplicação que provê recursos tanto para o gerenciamento quanto para a manipulação de IMs.

The proliferation of computer technology and digital image‐acquisition hardware has led to the widespread use of image data across a variety of applications including astronomy, art, natural resources, engineering design, military, business operation, medicine, education, etc. Major research activities in the digital image databases surged after the U.S. government's Digital Library Initiative (DLI) from 1994 to 1998. The DLI research team at the University of California at Berkeley developed a work‐centered digital information system that contains 450 digital text documents, 200 air photos, and over 11,000 ground photographs. The system allowed a user or a working group to access its own collections of varying data types, and to generate new materials to be added to the collection. The DLI project at the University of California (UC) at Santa Barbara focused on the development of digital databases that contain geographically referenced materials such as maps and aerial photos. The research team developed a number of tools for browsing and retrieving map images at multiple resolution. Two other major efforts in developing digital image databases were at The National Library of Medicine (NLM), a component of the National Institutes of Health (NIH), and at Time Warner. More recently, research scientists at the University of California at Berkeley and the Fine Arts Museums of San Francisco successfully launched on the Internet the largest art image database in the world, the Thinker ImageBase.Automatic image indexing and retrieving technology is fundamental in digital image databases. There are two general strategies in image retrieval, browsing and searching. Browsing is an information retrieval strategy in which a user navigates through an ordered arrangement of images by making selections from the progressive levels of a hierarchy into which the available images have been logically grouped. Image browsing relies on the user's cognitive abilities to recognize images of interest without having to formulate a specific query. Searching is an information retrieval strategy in which the user communicates with an information retrieval system by an interface that requires the user to input a search query.Images can be indexed and retrieved by text‐tag information and/or by image content. Conventionally, images are indexed using text‐tag information, such as title, key words, date of the work, artist, author, photographer, legend, captions, etc. Images are often subject to a wide range of interpretations, and textual descriptions can only begin to capture the richness and complexity of the semantic content of a visual image. In many applications, the complexity of the information embedded in image content such as types of objects, object attributes, and spatial relationship of objects, etc, cannot be synthesized in a few key words. It has been reported that users querying an image collection tend to be much more specific in their requests and information needs than when querying a text database. Furthermore, text indexing requires large human effort in creating the meta‐data that enables visual queries and is language dependent. Large databases containing thousands and millions of digital images that can occupy gigabytes of space are almost impossible for manual indexing and searching. The demand for systems using pictorial information combined with textual description in image retrieval is growing and automatic indexing and retrieval based on image content has become the most promising techniques for large image databases and digital image libraries. This article describes the techniques developed for content‐based retrieval.