Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/1859
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dc.contributor.authorParekh, Rupal-
dc.contributor.authorDr. Achyut C., Patel-
dc.date.accessioned2024-11-21T07:46:50Z-
dc.date.available2024-11-21T07:46:50Z-
dc.date.issued2020-
dc.identifier.issn1548-7741-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/1859-
dc.description.abstractThe use of digital medical imaging systems has greatly increased in healthcare institutions and they are currently valuable tools supporting medical decision and treatment procedures. NoSQL databases have been replacing relational databases in some scenarios, due to their horizontal scalability and to their flexibility to adapt to dynamic requirements. This research focus on DICOM images, as unstructured data as it is the standard used in healthcare industries. The fitness of NoSQL Databases in view of addressing all the challenges revolving around digital imaging is to be studied and analyzed. In this context, the performances of the Relational Data Model and the NoSQL Databases in storing and retrieving Medical Images are to be analyzed. We consider the many methods in handling digital images. For the experiment here in this research we consider MySQL as a RDBMS and MongoDB and Cassandra as NoSQL databases. We designed a set of experiments with a huge number of various aspects for storing and retrieving of digital images for the comparing two databases by the same data for RDBMS and NoSQL. The results show that NoSQL data model performs better for storing and retrieval of medical images.en_US
dc.language.isoenen_US
dc.publisherJournal of Information and Computational Scienceen_US
dc.relation.ispartofseries10;11-
dc.subjectNoSQLen_US
dc.subjectSQLen_US
dc.subjectRDBMSen_US
dc.subjectBig dataen_US
dc.subjectDatabaseen_US
dc.subjectMongoDBen_US
dc.subjectCassandraen_US
dc.subjectDICOMen_US
dc.subjectPACSen_US
dc.subjectPerformance evaluationen_US
dc.titlePerformance Evaluation of RDBMS with Several NoSQL Databases in aspect of Medical Imagesen_US
dc.typeArticleen_US
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