Survey on Cancer Detection using Content Based Image Retrieval Technique

Aparna W. Bondade, Priti Saktel

Abstract: With the increase use of medical images in clinical drug, disease do research, and education, the necessitate for methods with the purpose of efficiently archive, query, and retrieve these images by their content is underscored. In these paper, we illustrate the design and improvement of a multitier content-based image retrieval (CBIR) system for microscopic images utilize a location database that contains images of multi-disease of cancer. The CBIR system uses a multitier approach for retrieve and classify main type of cancer disease and subtype of main cancer disease, which are generally complicated to discriminate and categorize. This system enables both multi-image query and slide-level image retrieval in order to care for the semantic stability among the retrieved images. Weighting terms, motivated from information retrieval theory, are defined for more than one image query and retrieval. This system also used the histogram and object learning dictionary CBIR system can working efficiently.

Keywords: Content-based image retrieval CBIR, information retrieval IR, microscopy multi-image queries, weighting scores

How to Cite?: Aparna W. Bondade, Priti Saktel, "Survey on Cancer Detection using Content Based Image Retrieval Technique", Volume 3 Issue 11, November 2014, International Journal of Science and Research (IJSR), Pages: 1019-1020, https://www.ijsr.net/getabstract.php?paperid=OCT141074, DOI: https://dx.doi.org/10.21275/OCT141074

Download Citation: APA | MLA | BibTeX | EndNote | RefMan