An On-Line Medical Imaging Management for Shared Research in the Web using Pattern Features

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1 An On-Line Medical Imaging Management for Shared Research in the Web using Pattern Features Gustavo Molitor Porcides Terumi Kamada Gilson Antonio Giraldi National Laboratory for Scientific Computing Petropolis - RJ, Brazil Leandro Henrique Stein leandro.h.stein@gmail.com Luiz Antonio Pereira Neves neves@ufpr.br Abstract This work aims to create a medical and biological imaging management system that will be used to share images and information between researchers via a client/server architecture. It will be developed using the DBMS PostgreSQL and PHP to create the web interface. In this system the image attributes are automatically extracted and the pattern features are obtained by image retrieval techniques for improving the searches. These are the main advantages of the proposed solution. Finally, we also present the development methodology of the proposed tool. 1. Introduction The objective of this research is the development of a management system for medical and biological images that includes resources for edition, registration and classification of images. Moreover, the proposed system offers facilities to store results of processing tasks. In addition, it allows researchers to share information through the Web. The proposed system uses web tools so that the data base can be remotely accessed via a web browser. Therefore, we get high usability and interactivity, since web browsers are known and portable user interfaces. Many researchers have presented similar proposals in the literature. For instance, Azevedo-Marques et al [2] suggests the use of the PACS (Picture Archiving and Communication Systems), for storage, communication, processing and edition of medical images and diagnoses in hospitals. The proposed PACS system uses the DICOM standard for information trade between hospitals. It is composed of a DICOM server and web server. The use of web technologies, such as HTML and ASP, allows a fast distribution and friendly interface. The PACS utilizes a client/server architecture and data model made in Oracle and Delphi 5. In Azevedo-Marques et al [3], authors propose another kind of PACS for the Hospital das Clínicas from Ribeirão Preto (FMRP-USP). This model, uses a Linux server for image distribution through FTP using TCP/IP. The images are stored in disk-arrays or CD-ROM. The authors comment that the implementation of this system has a high cost and, for this reason, the implementation must be well planned. In another work, Pires et al [17] perform software developed with Delphi 6 and Interbase 6 using the BI-RADS standard ( Breast Imaging Reporting and Data System ) for the registration of mammographic images. This system offers image visualization and training facilities for students of the Federal University of São Paulo. For image retrieval Caritá et al [5] suggests the use of the CBIR (Content Based Image Retrieval). In this case, MySQL is used to store attributes like color, shape and texture. These features are extracted by a system component written in C++ that will verify the images in a PACS server. It has textual recovery with HTML and PHP and a Java software to visualize the DICOM images. On the other hand, d Ornellas et al [7] suggests the use of metadata from medical image. According to the W3C [6] definition, metadata are information located in the web, in- 36

2 telligible by the computer. So, the metadata is a data used to describe a primary data. Information attached to an image, or any other kind of document, are very useful for data recovery and search in a data base. However, they may be useless if they are not organized and structured. The use of metadata is very complex and requires many computational resources due to the construction of its meaning. A system of this nature is being developed by the PIGS group and will be implemented at the Santa Maria University Hospital (HUSM). Santos M. and Furuie S. [21] propose a management system in Java, with image processing algorithms for the storage and manipulation of medical images. The authors indicate an interactive architecture like an Internet portal, being useful as a tool for research, retrieval and data processing. The images are stored in a PostgreSQL 8.0 database. It can interact with other applications with distributed access based on P2P and client/server. The proposed system supports many digital image formats, such as: DICOM, TIFF, GIF, JPEG, BMP, etc. Marchiori P. Z. [12] suggests the use of virtual libraries to improve the process of management of information supported by data bases and web resources. Furthermore, they can access other libraries by the Internet, trading data through the use of protocols. Another advantage is the possibility of remote access, so a user can take part of a discussions and trade data with the library. The use of communication protocols becomes necessary to create a connection between data bases and virtual libraries. A communication protocol is a convention or pattern that controls and allows a connection and transference of data between two computer systems [23]. Simply, a protocol can be defined as the rules that control the syntax, semantic and synchronization of communication. The protocols can be implemented by the hardware, software or a combination of both. Rosetto M. [20] indicates the use of the Z39.50, a communication protocol that allows access to multiple systems using a single interface, with client/server technology operating over the Internet. Its goal is to simplify the manipulation of information in distributed systems. Brito [4] proposes the use of the system called MicroI- SIS. This system has fields that store digital images for your records. It simplifies the management of collections because it performs searches based on keywords. However, MicroI- SIS has problems when dealing with large databases. This research meets many challenges, such as: the lack of medical image data base standards, the great variability of image formats and the definition of a secure architecture with the main server. Therefore, the great challenge faced by our work is the development of a management system for storage, manipulation, and sharing of medical and biological images using web technologies. This work is organized as follows. The methodology is described in section 2. Next, in the section 3, the proposed system is analyzed. The conclusions are given in section Methodology The methodology applied in this work is organized in four stages, as shown in the Figure 1. Figure 1. Methodology applied for the system development First Stage: Definition of The Data Base Management System The first phase consists of choosing the Data Base Management System (DBMS) that will be used in this work. In this way, three freeware DBMS are analyzed and compared accordingly to the maximum table load and its features Second Stage: Data Modeling The second stage is the definition of the data model, using the UML tool to describe the input and output and relational modeling to identify all the system s information Third Stage: Implementation The third stage consists of the data model implementation, using the tools defined in stage 1 and the analyzes of the features of three biotechnology web data bases, NCBI (National Center for Biotechnology Information) [11], Soft- Berry [22] and Addgene [1]. 37

3 2.4. Fourth Stage: Validation Tests In the fourth stage tests are made to validate the system. For this phase, the validation protocol is defined via the methods proposed by Pressmann [19] and by the use of a checklist evaluation to identify the user s perception of the system. 3. Analysis of Obtained Results In this section the results of the methodology are presented Results of the Data Base Management System In this section the features of MySQL [16], FirebirdSQL [8] and PostgreSQL [18] are shown and comparisons are made between them. MySQL is a DBMS written in C and C++, multitask, focused in threads [6], multiuser, optimized for web applications, specially if used with PHP. It s easy to use and it is portable to most computer platform with support for several programming languages. It has an excellent performance and stability, and it can be used in critical mission systems [14]. PostgreSQL is client/server DBMS and has transactions, triggers, views, foreign key referential integrity and locking [6]. FirebirdSQL is a high performance relational DBMS with trigger and procedures support [9]. In table 1 the maximum table load sizes of the three analyzed DBMS are reported [13] [10] [15]. Maximum Table Load PostgreSQL MySQL FirebirdSQL Windows 32TB 2TB 32TB Linux 32TB 4TB 32TB Table 1. Maximum Table Load According to Table 1, PostgreSQL and FirebirdSQL has support to greater table loads, offering up to 32TB of physical space for each table As shown by Chen and Xie [6] PostgreSQL 8.2 supports more features than MySQL 5.0 and Firebird 2.0. It supports associated integrity, database transactions, unicode, indexes, temporary tables, table partion and clusters. Although MySQL supports many of these features, it doesn t have GiST index support. Firebird supports only associated integrity, database transactions and Unicode. Therefore, by using the information shown in table 1 and by analyzing the features that these data base management systems supports, PostgreSQL has been chosen as the DBMS to be used in this project due to a greater support to all the features required for the implementation of the proposed system Results of the Image Manager s Data Modeling The data base has been modeled in a way that users are divided in several levels by the actions of the administrator as moderator. Each one has an access level with its privileges, such as remove, add, modify or only visualize the images. Non-registered users can only view the images. On the registration, the user must insert his name, address, institution, password and Social Security Number. The image attributes are width, height, resolution, type of compression, format and the quantity and type of channels. These attributes may be used to index the images. These attributes will be extracted automatically during the upload. We have studied CBIR (Content-Based Image Retrieval) algorithms as alternative to help the search for images. The algorithm analyzes the actual contents of the image, such as keywords, tags and descriptions, rather than the metadata. The contents analyzed are colors, shapes, textures, or any other information that can be derived from the image itself. The main tables are image and historical. The first one will keep all the data about the images. The second one will combine the information about the user and operations to have a complete historical of the data base used. Figure 2 shows the relational model Implementation of the Proposed System During stage 3, a friendly user interface has been implemented, which looks like the ones used by the biotechnology information bases NCBI (National Center for Biotechnology Information) [11], SoftBerry [22] and Addgene [1]. NCBI and Addgene have a keyword search engine that simplifies the access to the content that the user wants to view. They also have menus divided in types categories as proteins and genes. NCBI has a How To page that shows to navigate through the web site and access the content in an easy and understandable way. Moreover, NCBI has a registration module that allows registered members to save their researches, results, citations and offers several search filters and other benefits. In SoftBerry s main page, the links to the latest case studies are shown, to make the access easier. These websites are shown in Figures 3, 4, and 5. These functionalities are implemented in the proposed system to facilitate the interaction between the researcher and the system, offering a pleasant, organized and objective environment. 38

4 Figure 2. Relational Model of the Proposed System Tests of Validation Figure 3. NCBI Webpage. For the system s validation, three test methods proposed by Pressman [19] will be used: black box test, white box test and real-time test. The black box test verifies if the input is adequately accepted and the output is correctly produced, moreover it verifies if the external information integrity is maintained. Three test methodologies are used. The equivalency partitioning divides the output domain in equivalency classes for tests. This minimizes the test cases, limiting each class to one case. The limit value analysis verifies the neighboring values, since many errors may occur in the input limits of a module. The white box test aims to define test cases that exercise specific blocks of code of the web interface. The control structure test verifies the logical conditions, the data flux test takes the variables locations to define several test paths and the execution paths that are tested. The real-time test takes into account the actions timing and aims to determine the reaction of the systems in several states that vary with the time and can make the results obtained vary too. The real-time tests are divided into four stages. The first one, called task test, each task is tested with white and black box test individually, revealing logical and function problems, but not behavioral or timing errors. During the second stage the system s behavior is simu- 39

5 Figure 6. Proposed Checklist. Figure 4. SoftBerry Webpage. Currently, the web interface is being developed using PHP language and integrated with PostgreSQL database management as illustrated in figure 7. Figure 5. Addgene Webpage. Figure 7. Proposed Web Application. lated using CASE (Computer-Aided software Engineering) tools to test the system s behavior as a consequence of external events. These events are tests to detect errors and flaws. After that they are tested in random sequences and frequencies. The intertask test, the third stage, is realized after the detection of behavioral and individual tasks errors. It aims to detect timing errors. Several tasks communicate among themselves with varying data and processing loads to detect synchronization errors. In the last stage, the software and hardware are integrated and then several tests are made to discover errors in the hardware/software interface. Besides these methods, checklist evaluation will be made to identify the acceptance rate of the system. This evaluation will made based on several questions about the system, as shown if Figure Conclusions This research presents a system for image sharing among researchers in the Web, using feature patterns from images. The proposed research has advantages over others because the attributes are extracted automatically, the pattern features are obtained by image retrieval techniques and image database is public for any researchers in Digital Image Processing. Therefore, this project innovates by allowing image research using its attributes and metadata, what makes the search more efficient and effective. Furthermore, the images stored in the proposed system are registered with a historical that simplifies the analysis of empirical results. In future studies, several other functionalities will be implemented, such as algorithms for image manipulation and Content-Based Image Retrieval for improving the searches. References [1] Addgene. Available on accessed on april 21th, [2] P. M. Azevedo-Marques, E. C. Caritá, A. A. Benedicto, and P. R. Sanches. Implantação de um ris/pacs no hospital das 40

6 clínicas de ribeirão preto: Uma solução baseada em web. Radiol Bras 2005, São Paulo, pages 37 43, [3] P. M. Azevedo-Marques, C. S. Trad, J. E. Júnior, and A. C. Santos. Implantação de um mini-pacs (sistema de arquivamento e distribuição de imagens) em hospital universitário. Radiol Bras 2001, São Paulo, pages , [4] C. J. Brito. Gerencia de bases de imagens usando microisis. [5] E. C. Caritá, E. Seraphim, M. O. Honda, and P. M. Azevedo- Marques. Implementaçã e avaliação de um sistema de gerenciamento de imagens médicas com suporte à recuperação baseada em conteúdo. Radiol Bras 2008, São Paulo, pages , [6] R. Chen and J. Xie. Open Source Approaches In Spatial Data Handling. Springer, New York. [7] M. C. d Ornellas, S. R. Mussoi, and A. P. Dias. Avaliação e gerenciamento de qualidade de metadados de imagens médicas. XVIII Congresso Brasileiro de Engenharia Biomédica Santa Maria, [8] FirebirdSQL. Available on accessed on april 25th, [9] FirebirdSQL. Available on accessed on april 26th, [10] FirebirdSQL. Available on accessed on may 4th, [11] N. N. C. for Biotechnology Information. Available on accessed on april 21th, [12] P. Z. Marchiori. Ciberteca ou biblioteca virtual: Uma perspectiva de gerenciamento de recursos de informação [13] A. Milani. PostgreSQL : Guia do Programador. Novatec, São Paulo, [14] MySQL. Available on accessed on april 26th, [15] MySQL. Available on accessed on may 4th, [16] MySQL. Available on accessed on april 25th, [17] S. R. Pires, R. B. Medeiros, and H. Schiabel. Banco de imagens mamográficas para treinamento na interpretação de imagens. Radiol Bras 2004, São Paulo, pages , [18] PostgreSQL. Available on accessed on april 25th, [19] R. S. Pressman. Engenharia de Software. Pearson Makron Books, São Paulo, [20] M. Rosetto. Uso do protocolo z39.50 para recuperção de informções em redes eletrônicas [21] M. Santos and S. S. Furuie. Base de imagens para avaliação de algoritmos de processamento de imagens médicas. IV SBQS - V Workshop de Informática Médica, [22] SoftBerry. Available on accessed on april 21th, [23] L. B. Sousa. Redes de Computadores: Guia Total. Editora Érica, São Paulo,

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