Semantic Representation of Radiotherapy data for effective data mining

ANDRE, DEKKER and GEETHA, MAHADEVAIAH and JOHAN VAN, SOEST and NARENDRANATH, UDUPA and R.V., PRASAD and SHYAM, VASUDEV RAO and Y.KIRAN, KUMAR (2016) Semantic Representation of Radiotherapy data for effective data mining. In: Fifth International Conference On Advances in Applied Science and Environmental Engineering - ASEE 2016, 12-13 March,2016, Kuala Lumpur, Malaysia.

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Abstract

Radiotherapy plays an important role in the treatment of cancer patients. As part of clinical workflow, patient has to undergo through diagnostic imaging procedures, which are used to identify the tumor location and size. Enormous amounts of data are generated during this procedure. The volume of medical information is so large and complex that it becomes difficult to mine for relevant information. The Digital Imaging and Communications in Medicine (DICOM) standard is widely used in medicine for storing and transmitting medical information. The DICOM-RT is the extension to DICOM standard, and dedicated to radiotherapy. In this paper, we propose a technique to store clinical relevant features from DICOM files using semantic concepts. The proposed technique defines a novel method to delayer the hierarchy of DICOM-RT for storing the clinical relevant information into triples in Resource Description Framework (RDF) repository. The methodology also proposes different combinations for storing data such as DICOM-RT with tumor information, DICOM-RT with pathology details. The proposed method uses the Semantic Web Technology to store and represent the information from DICOM-RT files along with into RDF graph and a data mining approach. Natural Language processing technique is used for the retrieval of data. We have evaluated our methodology qualitatively for 20 patients including combinations such as RTSTRUCT, tumor size data along with CT data, pathology information, by producing 25 varieties of different queries. We have analyzed quantitatively with accuracy of 90% for different hypothetical conditions using our proposed methodology.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: DICOM-RT, Semantic Web, RDF, SPARQL,Natural Language Processing.
Depositing User: Mr. John Steve
Date Deposited: 25 Mar 2019 12:15
Last Modified: 25 Mar 2019 12:15
URI: http://publications.theired.org/id/eprint/948

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