CT brain image advancement for ICH diagnosis

Healthcare Technology Letters

article

Nor Shahirah Shaik Amir¹  Law Zhe Kang²  Shahizon Azura Mukari²  Ramesh Sahathevan³  Kalaivani Chellappan¹ 

[1] Department of Electric, Electronics and System, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia;Department of Neurology and Radiology, Universiti Kebangsaan Malaysia Medical Centre;Department of Internal Medicine Services, Ballarat Base Hospital, Ballarat Health Services;Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne;Florey Institute of Neuroscience and Mental Health

关键词: image denoising;    image segmentation;    Wiener filters;    computerised tomography;    brain;    medical image processing;    image enhancement;    CT brain image advancement;    ICH diagnosis;    primary intracerebral haemorrhage;    computed tomography brain images;    correct diagnosis;    imaging modality;    enhancement algorithm;    CT images;    CT brain images;    final diagnosis;    primary ICH;    UKM Medical Centre;    Digital Imaging;    main sections;    Wiener filter;    wavelet;    image enhancement;    modified unsharp masking algorithm;    UM algorithm;    image analysis;   

DOI  :  10.1049/htl.2018.5003

学科分类：肠胃与肝脏病学

来源: Wiley

【 摘 要 】

A critical step in detection of primary intracerebral haemorrhage (ICH) is an accurate assessment of computed tomography (CT) brain images. The correct diagnosis relies on imaging modality and quality of acquired images. The authors present an enhancement algorithm which can improve the clarity of edges on CT images. About 40 samples of CT brain images with final diagnosis of primary ICH were obtained from the UKM Medical Centre in Digital Imaging and Communication in Medicine format. The images resized from 512 × 512 to 256 × 256 pixel resolution to reduce processing time. This Letter comprises of two main sections; the first is denoising using Wiener filter, non-local means and wavelet; the second section focuses on image enhancement using a modified unsharp masking (UM) algorithm to improve the visualisation of ICH. The combined approach of Wiener filter and modified UM algorithm outperforms other combinations with average values of mean square error, peak signal-to-noise ratio, variance and structural similarity index of 2.89, 31.72, 0.12 and 0.98, respectively. The reliability of proposed algorithm was evaluated by three blinded assessors which achieved a median score of 65%. This approach provides reliable validation for the proposed algorithm which has potential in improving image analysis.

【 授权许可】

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