Effect of Hybrid Data Compression Technique on the Diagnostic Accuracy of Region of Interest (ROI) on MRI Image of a Spine Disc Prolapse

dc.contributor.authorOyeleke, Richard O.
dc.contributor.authorAdewole, Adetunji P.
dc.contributor.authorOladeji, Florence A.
dc.date.accessioned2019-09-27T07:30:24Z
dc.date.available2019-09-27T07:30:24Z
dc.date.issued2014-07
dc.description.abstractThe cost of transmitting and archiving medical images are quite prohibitive due to their large sizes especially in digital radiology system such as: picture archiving and communication systems and teleradiology. In order to reduce storage requirements and improve transmission rate, there is need for compression. Usually, radiologists are only interested in the abnormal region of the image (known as the region of interest) in making diagnosis and interpretations; hence, this work investigates the effect of hybrid data compression technique on the diagnostic accuracy of region of interest (ROI) on magnetic resonance image (MRI) of a spine disc prolapsed. We extract the ROI from the original image and apply lossless Wavelet-Based Compression (WBC) on the ROI while the remainder image known as the non-region of interest is compressed using discrete cosine transform (DCT). A compression ratio of 7:1 was achieved. Finally, the diagnostic accuracy of the compressed ROI image was evaluated subjectively by a group of 30 evaluators comprising of 20 radiologists and 10 Radiographers. The results obtained show a 100% acceptance of the compressed ROI for healthy diagnosis and interpretation.en_US
dc.identifier.citationOyeleke, Richard O., Adewole, Adetunji P., Oladeji, Florence A. (2014). Effect of Hybrid Data Compression Technique on the Diagnostic Accuracy of Region of Interest (ROI) on MRI Image of a Spine Disc Prolapse. International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868. Foundation of Computer Science FCS, New York, USA. 7(5): 16-20en_US
dc.identifier.issn2249-0868
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/6178
dc.language.isoenen_US
dc.publisherInternational Journal of Applied Information Systemsen_US
dc.relation.ispartofseries7;5
dc.subjectImage compressionen_US
dc.subjectmedical imageen_US
dc.subjectregion of interesten_US
dc.subjectimage evaluationen_US
dc.subjectdiagnostic accuracyen_US
dc.titleEffect of Hybrid Data Compression Technique on the Diagnostic Accuracy of Region of Interest (ROI) on MRI Image of a Spine Disc Prolapseen_US
dc.typeArticleen_US
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