MR image enhancement for ICH classification

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Intracerebral hemorrhage (ICH) and cerebral amyloid angiopathy (CAA) are two common causes of hemorrhagic stroke. Distinguishing CAA from ICH is challenging due to similarities in clinical presentation and imaging. Magnetic Resonance Imaging (MRI) is one imaging modality that can be used in the early detection of ICH. The objective of this paper is to identify the best enhancement techniques in MR images for ICH classification. 5 samples of MR images with a final diagnosis of primary ICH (pICH) were selected from UKM Medical Centre (UKMMC). The MR images which were in Digital Imaging and Communications in Medicine (DICOM) format were later processed using the Matrix Laboratory (MATLAB) software. In this study 5 MR images from 5 different patients were processed using 4 image enhancement techniques; power law transformation histogram equalization image sharpening and median filter. All the 5 processed images were compared to obtain the best enhanced images based on their Absolute Mean Brightness Error (AMBE) and entropy values. Median filter is the best image enhancement technique with average values of AMBE and entropy of 0.0885 and 5.1472.

Original languageEnglish
Title of host publicationIECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages160-165
Number of pages6
ISBN (Electronic)9781467377911
DOIs
Publication statusPublished - 3 Feb 2017
Event2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016 - Kuala Lumpur, Malaysia
Duration: 4 Dec 20168 Dec 2016

Other

Other2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016
CountryMalaysia
CityKuala Lumpur
Period4/12/168/12/16

Fingerprint

hemorrhages
Median filters
image enhancement
Image enhancement
Luminance
Entropy
Digital Imaging and Communications in Medicine (DICOM)
Imaging techniques
brightness
entropy
filters
Amyloid
strokes
medicine
histograms
format
magnetic resonance
communication
computer programs
augmentation

Keywords

  • cerebral amyloid angiopathy
  • DICOM
  • hypertension
  • image enhancement
  • intracerebral hemorrhage
  • magnetic resonance imaging

ASJC Scopus subject areas

  • Biomedical Engineering
  • Instrumentation

Cite this

Amir, N. S. B. S., Chell, K., Law, Z. K., Mohamed Mukari, S. A., & Sahathevan, R. (2017). MR image enhancement for ICH classification. In IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences (pp. 160-165). [7843435] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECBES.2016.7843435

MR image enhancement for ICH classification. / Amir, Nor Shahirah Binti Shaik; Chell, Kalaivani; Law, Zhe Kang; Mohamed Mukari, Shahizon Azura; Sahathevan, Ramesh.

IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc., 2017. p. 160-165 7843435.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Amir, NSBS, Chell, K, Law, ZK, Mohamed Mukari, SA & Sahathevan, R 2017, MR image enhancement for ICH classification. in IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences., 7843435, Institute of Electrical and Electronics Engineers Inc., pp. 160-165, 2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016, Kuala Lumpur, Malaysia, 4/12/16. https://doi.org/10.1109/IECBES.2016.7843435
Amir NSBS, Chell K, Law ZK, Mohamed Mukari SA, Sahathevan R. MR image enhancement for ICH classification. In IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc. 2017. p. 160-165. 7843435 https://doi.org/10.1109/IECBES.2016.7843435
Amir, Nor Shahirah Binti Shaik ; Chell, Kalaivani ; Law, Zhe Kang ; Mohamed Mukari, Shahizon Azura ; Sahathevan, Ramesh. / MR image enhancement for ICH classification. IECBES 2016 - IEEE-EMBS Conference on Biomedical Engineering and Sciences. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 160-165
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