CONTENT BASED MEDICAL IMAGE RETRIEVAL USING EFFICIENT MANIFOLD RANKING
DESIGN DETAILS
Graph-Based ranking models have been deeply studied and widely applied in information retrieval area. This this Matlab design focus on the problem of applying a novel and efficient graph-based model for content-based image retrieval (CBIR), especially for medical images.
Manifold Ranking (MR) a famous graph-based ranking model, ranks data samples with respect to the intrinsic geometrical structure collectively revealed by a large amount of data. It is exactly in line with our consideration. MR has been widely applied in many applications and shown to have excellent performance and feasibility on a variety of data types, such as the text, image and video. By taking the underlying structure into account, manifold ranking assigns each data sample a relative ranking score, instead of an absolute pairwise similarity as traditional ways. The score is treated as a similarity metric defined on the manifold, which is more meaningful to capturing the semantic relevance degree.
In this design the extend of the original manifold ranking which is named as Efficient Manifold Ranking (EMR). Specifically, we build an anchor graph on the database instead of a traditional k-nearest neighbor graph and design a new form of adjacency matrix utilized to speed up the ranking. An approximate method is adopted for efficient out-of-sample retrieval. The model has two separate stages: an offline stage for building (or training) the ranking model and an online/offline stage for handling a new testing.
REFERENCES
Reference Paper-1: EMR: A Scalable Graph-based Ranking Model for Content-based Image Retrieval
Author’s Name: Bin Xu, Jiajun Bu, Chun Chen, Can Wang, Deng Cai, Member, and Xiaofei He
Source: IEEE
Year: 2015
Request source code for academic purpose, fill REQUEST FORM below,
http://www.verilogcourseteam.com/requ...
You may contact +91 7904568456 by WhatsApp Chat, for paid services.
We are available on Telegram and Signal.
Visit Website: http://www.verilogcourseteam.com/
Visit Our Social Media
Like our Facebook Page: / verilogcourseteam
Subscribe: / verilogcourseteamelectricalprojects
Subscribe: / verilogcourseteammatlabproject
Subscribe: / verilogcourseteam