NDLI: A medical image retrieval scheme through a medical social network

Content Provider	Springer Nature Link
Author	Bouslimi, Riadh Akaichi, Jalel Ayadi, Mouhamed Gaith
Copyright Year	2016
Abstract	Medical social networking sites have enabled multimedia content sharing in large volumes by allowing physicians and patients to upload their medical images. Moreover, it is necessary to employ new techniques to effectively handle and benefit from them. This huge volume of images needs to formulate new types of queries that pose complex questions to medical social network databases. Content-based image retrieval (CBIR) stills an active and efficient research topic to manipulate medical images. To palliate this situation, we propose in this paper the integration of a content-based medical image retrieval method through a medical social network, based on an efficient fusion of low-level visual image features (color, shape and texture features) which offers an efficient and flexible precision. A clear application of our CBIR system consists of providing stored images that are visually similar to a new (undiagnosed) one, allowing specialist and patients to check past exam diagnoses from comments and other physicians’ annotations, and to establish, therefore, a new diagnostic or to prepare a new report of an image’s exam. Experiments show that the proposed medical image retrieval scheme achieves better performance and accuracy in retrieving images. However, we need also to verify whether our approach is considered by the specialists as a potential aid in a real environment. To do so, we evaluate our methodology’s impact in the user’s decision, inquiring the specialists about the degree of confidence in our system. By analyzing the obtained results, we can argue that the proposed methodology presented a high acceptance regarding the specialists’ interests in the clinical practice domain and can improve the decision-making process during analysis.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	21926662
Journal	Network Modeling Analysis in Health Informatics and Bioinformatics
Volume Number	5
Issue Number	1
e-ISSN	21926670
Language	English
Publisher	Springer Vienna
Publisher Date	2016-06-20
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Computational Biology/Bioinformatics Feature extraction Health Informatics Bioinformatics Content-based medical image retrieval (CBMIR) Medical social network Applications of Graph Theory and Complex Networks
Content Type	Text
Resource Type	Article
Subject	Urology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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