Multiple Ranks Weighting Score for Microscopic Image Retrieval System
Автор: P. Suresh, L. Malliga, M. Vijay
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 10 Vol. 6, 2014 года.
Бесплатный доступ
Content based medical images have become a major necessity with the growing retrieving Advancements. CBIR access to medical images for supporting clinical decision making has been proposed that would be ease to manage large number of image in the database system. [4] In real time case only few systems has been developed and used in clinical environment. Content-Based Image Retrieval refers to image retrieval system that is based on visual properties of image objects other than textual annotation. Query image features compare with the database image features which is not exactly matching so image feature can be compare with the two tier approach in the database image in order to improve the accuracy of the retrieval system. Every day, large volume of different types of medical images such as MRI, CT images ultrasound, x-ray, radiology, etc are produced in different medical centre’s .microscopic image classification and discrimination (sub-type) [12] is the most difficult problem in medical image retrieval system. In this paper, the survey provides the suitable algorithm for retrieval and classification of medical image to improve the overall accuracy of the MIMS.
Content Based Image Retrieval (CBIR), Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Medical Image Management System (MIMS)
Короткий адрес: https://sciup.org/15012173
IDR: 15012173
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