2CSIO, Sector 20, Chandigarh, 3Landran Engg. College, Mohali

Abstract

Content-based image retrieval (CBIR) has been one the most vivid research areas in the field of computer vision, and substantial progress have been made over the last years.  CBIR has a potential for making a strong impact in diagnostics, research, and education.  CBIR is a promising technology to enrich the core functionality of picture archiving and communication systems (PACS). Even in modern PACS that are based on the Digital Imaging and Communications in Medicine (DICOM) standard, image data is addressed by alphanumerical indexes such as patient name and examination date. The main purpose of this paper is to disseminate the knowledge of the CBIR approach to the applications of medical image retrieval and to attract greater interest from various research communities to rapidly advance research in this field. 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 Content based medical image retrieval (CBMIR) research. Also, several research directions for improving the retrieval quality based on the experiences from other closely related research fields are given in the paper. Possible clinical benefits from the use of content-based access methods are described as well as promising fields of applications.

 Keywords: Content based medical image retrieval (CBMIR), National Health and Nutrition Examination Survey (NHANES), National Library of Medicine (NLM), Pathology bearing region (PBR), Picture archiving and communication systems (PACS), Region of interest (ROI).

 (P1150845461, 1.26MB)