A comprehensive survey on content based image retrieval system and its application in medical domain

  • Authors

    • K Srinivasa Reddy
    • R Anandan
    • K Kalaivani
    • P Swaminathan
    2018-05-29
    https://doi.org/10.14419/ijet.v7i2.31.13436
  • CBIR, image retrieval, feature extraction, medical images.

  • Abstract

    Content Based Image Retrieval (CBIR) is an important and widely used technique for retrieval of different kinds of images from large database. Collection of information in database are available in different formats such as text, image, graph, chart etc. Here, our focus is on information which is available in the form of images. Searching and retrieval of the image from a large amount of database is difficult problem because it uses the image visual information such as shape, text and color for indexing and representation of an image. For efficient CBIR system, there is a need to develop different kinds of retrieval methods using feature extraction, similarity matching etc. Text Based Image Retrieval systems are used in many hospitals, but for large databases these are inefficient. To solve this problem, CBIR systems are proposed to retrieve matching images from database using automated feature extraction method. At present, medical imaging field finds extensive growth in the generation and evaluation of various types of medical images which are high inconsistency, usually fused and the combination of various minor composition structures. For easy retrieval, need to be development of feature extraction and image classification methods. Different methods are used for different kinds of medical images. The Radiology department and Cardiology department are the largest producers of medical images and the patient abnormal images can be stored with the normal images. CBIR uses query image as input and it retrieves the images, which are similar to the query more efficiently and effectively. This paper provides a comprehensive Survey about CBIR system and its one of the major application in medical domain.

     

     

  • References

    1. [1] Ananth Raj P & Venkataramana A, “Krawtchouk Chromaticity Distribution Moments for Content Based Image Retrievalâ€, NCC IIT Guwahati, (2009).

      [2] Cai W, Liu S, Wen L, Eberl S, Fulham MJ & Feng D, “3D neurological image retrieval with localized pathology-centric CMRGlc patternsâ€, 17th IEEE International Conference on Image Processing (ICIP), (2010), pp.3201-3204.

      [3] Oberoi A & Singh M, “Content Based Image Retrieval system for Medical Data bases (CBIR-MD)-Lucratively tested on Endoscopy, Dental and skull imagesâ€, International Journal of Computer Science Issues, Vol.9, No.3, (2012).

      [4] Laban N, ElSaban M, Nasr A & Onsi H, “System refinement for content based satellite image retrievalâ€, The Egyptian Journal of Remote Sensing and Space Science, Vol.15, No.1, (2012), pp.91-97.

      [5] Singh J, Kaleka JS & Sharma R, “Different approaches of CBIR Techniquesâ€, International Journal of Computers & Distributed systems, Vol.1, No.2, (2012).

      [6] Fanid FAthabad Y & Balafar MA, ‘Application of content based image retrieval in diagnosis brain diseaseâ€, International Journal on Technical and physical problems of Engineering, Vol.4, No.13, (2012), pp.133-138.

      [7] Senthil Kumar R & Senthilmurugan M, “Content based Image retrieval system in medical applicationsâ€, International Journal of Engineering Research & Technology, Vol.2, No.3, (2013).

      [8] Solio AA & Ladhake SA, “A review of query image in content based image retrievalâ€, International Journal of Advanced Research in Computer Engineering & Technology, Vol.2, No.4, (2013).

      [9] Bhende P & Cheran AN, “Content based image retrieval in Medical Imagingâ€, International journal of computational Engineering and Research, Vol.3, No.8, (2013).

      [10] Mahajan AR, Zade SD & Raut P, “Content based image retrieval in medical images: current-status and future directionsâ€, International Journal of Application or Innovation in Engineering & Management, Special issue for National Conference on Recent advances in technology and management for integrated growth, (2013).

      [11] Neha, “Content-Based Image Retrieval: A Reviewâ€, International Journal of Science, Engineering and Technology Research, Vol.3, No.5, (2014).

      [12] Yadav AM & Sengar BPS, “A survey on content based image retrieval systemsâ€, International Journal of Emerging Technology and Advanced Engineering, Vol.4, No.6, (2014).

      [13] Singh A, Shohani P & Kumar M, “A Review of Different Content Based Image Retrieval Techniquesâ€, International Journal of Engineering Research and general science, Vol.2, No.5, (2014).

      [14] Shukla J & Vania J, “A survey on CBIR Feature Extraction Techniquesâ€, International Journal of Engineering and Computer Science, Vol.3, No.12, (2014), pp.9555-9559.

      [15] Mansourvar M & Ismail MA, “Content based image retrievalâ€, International Journal of Information Technology, Vol.20, No.2, (2014).

      [16] Abed MH & Al-Farhoosi Iraq DSJ, “Content based image retrieval based on Histogramâ€, International Journal of Computer applications, Vol.110, No.3, (2015).

      [17] Haldurai L & Vinodhini V, “A study on content based image retrieval systemsâ€, International Journal of Innovative Research in Computer and Communication Engineering, Vol.3, No.3, (2015).

      [18] Arya D & Jha J, “A review on content based image retrieval using feature extractionâ€, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.6, No.3, (2016).

      [19] Banuchitra S & Kungumaraj K, “A Comprehensive Survey of Content Based Image Retrieval Techniquesâ€, International Journal of Engineering and Computer Science, Vol.5, No.8, (2016), pp.17577-17584.

      [20] Abuein QQ, Batiha R, Shatnawi MQ, Al-Aiad A & Amareen S, “Content Based Image Retrieval for Medical Applications with Flip-Invariant Consideration using Low-Level Descriptorsâ€, International Journal of Advanced Computer Science and Applications, Vol.7, No.4, (2016).

      [21] da Silva Torres R & Falcao AX, “Content-based image retrieval: theory and applicationsâ€, RITA, Vol.13, No.2, (2006), pp.161-185.

      [22] Müller H, Michoux N, Bandon D & Geissbuhler A, “A review of content-based image retrieval systems in medical applications-clinical benefits and future directionsâ€, International journal of medical informatics, Vol.73, No.1,(2004), pp.1-23.

      [23] Antani SK, Deserno TM, Long LR, Güld MO, Neve L & Thoma GR, “Interfacing global and local CBIR systems for medical image retrievalâ€, Bildverarbeitung für die Medizin, (2007), pp.166-171.

      [24] Uwimana E & Ruiz ME, “Automatic classification of medical images for content based image retrieval systemâ€, Proceedings of the AMIA Annual Symposium, (2008), pp.1159-1165.

      [25] da Silva Júnior JA, Marçal RE & Batista MA, “Image Retrieval: Importance and Applicationsâ€, Workshop de Vis~ao Computacional-WVC, (2014).

      [26] Raisi Z, Mohanna F & Rezaei M, “Applying Content-Based Image Retrieval Techniques to Provide New Services for Tourism Industryâ€, International Journal of Advanced Networking and Applications, Vol.6, No.2, (2014), pp.2222-2232.

  • Downloads

  • How to Cite

    Srinivasa Reddy, K., Anandan, R., Kalaivani, K., & Swaminathan, P. (2018). A comprehensive survey on content based image retrieval system and its application in medical domain. International Journal of Engineering & Technology, 7(2.31), 181-185. https://doi.org/10.14419/ijet.v7i2.31.13436

    Received date: 2018-05-29

    Accepted date: 2018-05-29

    Published date: 2018-05-29