A Content-Based Approach to Medical Image Database Retrieval

Content-based image retrieval (CBIR) makes use of image features, such as color and texture, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. This chapter introduces a content-based approach to medical image retrieval. Fundamentals of the key components of content-based image retrieval systems are introduced first to give an overview of this area. A case study, which describes the methodology of a CBIR system for retrieving digital mammogram database, is then presented. This chapter is intended to disseminate the knowledge of the CBIR approach to the applications of medical image management and to attract greater interest from various research communities to rapidly advance research in this field.

[1]  S.T.C. Wong.  CBIR in medicine: still a long way to go , 1998, Proceedings. IEEE Workshop on Content-Based Access of Image and Video Libraries (Cat. No.98EX173).

[2]  John P. Eakins,et al.  Towards intelligent image retrieval , 2002, Pattern Recognit..

[3]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[4]  Yong Rui,et al.  LEARNING BASED RELEVANCE FEEDBACK IN IMAGE RETRIEVAL , 2002 .

[5]  Mingjing Li,et al.  Color texture moments for content-based image retrieval , 2002, Proceedings. International Conference on Image Processing.

[6]  Usha Sinha,et al.  Principal component analysis for content-based image retrieval. , 2002, Radiographics : a review publication of the Radiological Society of North America, Inc.

[7]  John S. Erickson.  Database Technologies: Concepts, Methodologies, Tools, and Applications (4 Volumes) , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[8]  Chang-Tsun Li,et al.  Unsupervised texture segmentation using multiresolution Markov random fields , 1998 .

[9]  Nikolas P. Galatsanos,et al.  Relevance feedback based on incremental learning for mammogram retrieval , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[10]  Nicu Sebe,et al.  Color-based retrieval , 2001, Pattern Recognit. Lett..

[11]  James Bradley.  An Object-Relationship Diagrammatic Technique for Object-Oriented Database Definitions , 1992 .

[12]  Shamik Sural,et al.  Similarity between Euclidean and cosine angle distance for nearest neighbor queries , 2004, SAC '04.

[13]  C KakAvinash,et al.  Using human perceptual categories for content-based retrieval from a medical image database , 2002 .

[14]  Theo Gevers,et al.  Classifying color edges in video into shadow-geometry, highlight, or material transitions , 2003, IEEE Trans. Multim..

[15]  Joaquim A. Jorge,et al.  Indexing high-dimensional data for content-based retrieval in large databases , 2003, Eighth International Conference on Database Systems for Advanced Applications, 2003. (DASFAA 2003). Proceedings..

[16]  J. J. Rocchio,et al.  Relevance feedback in information retrieval , 1971 .

[17]  Carla E. Brodley,et al.  Using Human Perceptual Categories for Content-Based Retrieval from a Medical Image Database , 2002, Comput. Vis. Image Underst..

[18]  Hamid Abrishami Moghaddam,et al.  A new algorithm for image indexing and retrieval using wavelet correlogram , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[19]  Seiichi TAMAI.  The Color of Digital Imaging in Pathology and Cytology , 2001 .

[20]  L. Rodney Long,et al.  Partial shape matching for CBIR of spine x-ray images , 2003, IS&T/SPIE Electronic Imaging.

[21]  Ian W. Ricketts,et al.  The Mammographic Image Analysis Society digital mammogram database , 1994 .

[22]  Sudha Ram,et al.  A Comprehensive Framework Towards Information Sharing Between Government Agencies , 2007, Int. J. Electron. Gov. Res..

[23]  Shigeo Wada,et al.  Flexible color texture retrieval method using multi-resolution mosaic for image classification , 2002, 6th International Conference on Signal Processing, 2002..

[24]  Antoine Rosset,et al.  Comparing features sets for content-based image retrieval in a medical-case database , 2004, SPIE Medical Imaging.

[25]  Carla E. Brodley,et al.  ASSERT: A PHYSICIAN-IN-THE-LOOP CONTENT-BASED IMAGE RETRIEVAL SYSTEM FOR HRCT IMAGE DATABASES , 1999 .

[26]  Henri A. Vrooman,et al.  Suitability of texture features to assess changes in trabecular bone architecture , 2002, Pattern Recognit. Lett..

[27]  Xin Luo,et al.  Encyclopedia of Multimedia Technology and Networking , 2008 .

[28]  Philip Calvert,et al.  Encyclopedia of Database Technologies and Applications , 2005 .

[29]  Wan-Chi Siu,et al.  Multimedia Information Retrieval and Management: Technological Fundamentals and Applications , 2010 .

[30]  Remco C. Veltkamp,et al.  State of the Art in Shape Matching , 2001, Principles of Visual Information Retrieval.

[31]  Nikolas P. Galatsanos,et al.  A similarity learning approach to content-based image retrieval: application to digital mammography , 2004, IEEE Transactions on Medical Imaging.

[32]  Pong C. Yuen,et al.  Regularized color clustering in medical image database , 2000, IEEE Transactions on Medical Imaging.

[33]  Ömer Egecioglu,et al.  Dimensionality reduction and similarity computation by inner-product approximations , 2000, IEEE Transactions on Knowledge and Data Engineering.

[34]  H. K. Huang.  PACS, Image Management, and Imaging Informatics , 2003 .

[35]  Manhoi Choy,et al.  Distributed Database Design for Mobile Geographical Applications , 2000, J. Database Manag..

[36]  G. Tourassi.  Journey toward computer-aided diagnosis: role of image texture analysis. , 1999, Radiology.

[37]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .

[38]  L. Rodney Long,et al.  Evaluation of shape similarity measurement methods for spine X-ray images , 2004, J. Vis. Commun. Image Represent..

[39]  Hans-Peter Kriegel,et al.  The R*-tree: an efficient and robust access method for points and rectangles , 1990, SIGMOD '90.

[40]  O. Ratib,et al.  Integration of a multimedia teaching and reference database in a PACS environment. , 2002, Radiographics : a review publication of the Radiological Society of North America, Inc.

[41]  Gerard Salton,et al.  The SMART Retrieval System—Experiments in Automatic Document Processing , 1971 .

[42]  Antonin Guttman,et al.  R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.

[43]  Thierry Pun,et al.  Design and evaluation of a content-based image retrieval system , 2001 .

[44]  Marin Ferecatu,et al.  Sample Selection Strategies for Relevance Feedback in Region-Based Image Retrieval , 2004, PCM.

[45]  Norimichi Tsumura,et al.  Why Multispectral Imaging In Medicine , 2004 .

[46]  Dacheng Tao,et al.  Random sampling based SVM for relevance feedback image retrieval , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[47]  David E. Booth,et al.  Multivariate statistical inference and applications , 1997 .

[48]  Yap-Peng Tan,et al.  A novel multi-scale spatial-color descriptor for content-based image retrieval , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[49]  Amel Grissa Touzi,et al.  How to Achieve Fuzzy Relational Databases Managing Fuzzy Data and Metadata , 2008, Handbook of Research on Fuzzy Information Processing in Databases.

[50]  Antoine Geissbühler,et al.  A Review of Content{Based Image Retrieval Systems in Medical Applications { Clinical Bene(cid:12)ts and Future Directions , 2022 .

[51]  Yves Vander Haeghen,et al.  An imaging system with calibrated color image acquisition for use in dermatology , 2000, IEEE Transactions on Medical Imaging.

[52]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[53]  Johan Montagnat,et al.  Texture based medical image indexing and retrieval: application to cardiac imaging , 2004, MIR '04.

[54]  R. Nedunchezhian,et al.  Soft Computing Applications for Database Technologies: Techniques and Issues , 2010 .

[55]  Chang-Tsun Li,et al.  Design of Content-based Multimedia Retrieval , 2005 .

[56]  Luigi Portinale,et al.  Cased-Based Reasoning for medical knowledge-based systems , 2001, Int. J. Medical Informatics.

[57]  John M. Artz.  A crash course in metaphysics for the database designer , 1997 .

[58]  H. D. Cheng,et al.  Mass lesion detection with a fuzzy neural network , 2004, Pattern Recognit..

[59]  Sherif Sakr,et al.  Graph Data Management: Techniques and Applications , 2011, Graph Data Management.

[60]  Jorge Horacio Doorn,et al.  Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends , 2009 .

[61]  Nicu Sebe,et al.  Texture Features for Content-Based Retrieval , 2001, Principles of Visual Information Retrieval.

[62]  S. Majumdar,et al.  High-resolution magnetic resonance imaging: three-dimensional trabecular bone architecture and biomechanical properties. , 1998, Bone.

[63]  Vittorio Castelli,et al.  Image Databases: Search and Retrieval of Digital Imagery , 2002 .

[64]  Bor-Wen Cheng,et al.  Using case-based reasoning to establish a continuing care information system of discharge planning , 2004, Expert Syst. Appl..

[65]  Paul Over,et al.  TRECVID: Benchmarking the Effectivenss of Information Retrieval Tasks on Digital Video , 2003, CIVR.

[66]  Uwe Just,et al.  An accurate method for correction of head movement in PET , 2004, IEEE Transactions on Medical Imaging.

[67]  Marin Ferecatu,et al.  Retrieval of difficult image classes using svd-based relevance feedback , 2004, MIR '04.

[68]  Thomas Martin Deserno,et al.  Similarity of Medical Images Computed from Global Feature Vectors for Content-Based Retrieval , 2004, KES.

[69]  Berthold B Weinb,et al.  Integration of Content-based Image Retrieval to Picture Archiving and Communication Systems , 2003 .

[70]  Syed M Rahman.  Design and Management of Multimedia Information Systems: Opportunities and Challenges , 2000 .

[71]  Dah-Jye Lee,et al.  Evaluation of shape indexing methods for content-based retrieval of x-ray images , 2003, IS&T/SPIE Electronic Imaging.

[72]  Kaizhu Huang,et al.  Biased support vector machine for relevance feedback in image retrieval , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[73]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[74]  V. Serdobolʹskiĭ.  Multivariate statistical analysis : a high-dimensional approach , 2000 .

[75]  Rafael A. Calvo,et al.  Fast Dimensionality Reduction and Simple PCA , 1998, Intell. Data Anal..

[76]  Iris Reinhartz-Berger,et al.  Semi-Automatic Composition of Situational Methods , 2011, J. Database Manag..

[77]  Thierry Pun,et al.  Content-based query of image databases: inspirations from text retrieval , 2000, Pattern Recognit. Lett..

[78]  José Galindo,et al.  Handbook of Research on Fuzzy Information Processing in Databases , 2008, Handbook of Research on Fuzzy Information Processing in Databases.

[79]  Kari Smolander,et al.  Conflicts, Compromises, and Political Decisions: Methodological Challenges of Enterprise-Wide E-Business Architecture Creation , 2009, Int. J. Enterp. Inf. Syst..

[80]  Cheng-Seen Ho,et al.  A new hybrid case-based architecture for medical diagnosis , 2004, Inf. Sci..

[81]  James E. Wyse.  The Linkcell Construct and Location-Aware Query Processing for Location-Referent Transactions in Mobile Business , 2009 .

[82]  Thomas Martin Deserno,et al.  IRMA - Content-Based Image Retrieval in Medical Applications , 2004, MedInfo.

[83]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..