A Methodical Study of Content Based Medical Image Retrieval in Current Days

B. Satish
B. Satish
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Dr. Supreethi K. P
Dr. Supreethi K. P
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Jawaharlal Nehru Technological University, Hyderabad

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A Methodical Study of Content Based Medical Image Retrieval in Current Days

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Abstract

Content-based image retrieval (CBIR) is standout amongst the most rich research fields in the area of computer vision & significant advancement has been made throughout the decade. CBIR is an image search methodology that changed the traditional text-based retrieval of images by utilizing various visual features, for example, color, texture, & shape, as criteria of search. In the area of medical, images, particularly digital images, are generated in constantly increasing quantities & utilized for diagnostics & therapy. Content based approaches into medical images to support in making clinical decision has been suggested that would simplify the management of clinical data & scenarios to incorporate the content-based approaches. As, the total quantity of data generated in diagnostic centers has increased, it leads to the utilization of CBIR in the daily routine of hospitals & clinics.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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How to Cite This Article

B. Satish. 2016. \u201cA Methodical Study of Content Based Medical Image Retrieval in Current Days\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 16 (GJCST Volume 16 Issue F2).

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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  • Submission ReceivedDecember 8, 2015
  • Peer Review Double Blind
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  • Accepted December 31, 2015
  • Published January 15, 2016
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A Methodical Study of Content Based Medical Image Retrieval in Current Days

B. Satish
B. Satish <p>Jawaharlal Nehru Technological University, Hyderabad</p>
Dr. Supreethi K. P
Dr. Supreethi K. P
  • Submission ReceivedDecember 8, 2015
  • Peer Review Double Blind
    Handling Editor
  • Accepted December 31, 2015
  • Published January 15, 2016

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