| Efficient Denoising Technique for CT images to Enhance Brain Hemorrhage Segmentation. | |
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MedLine Citation:
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PMID: 22274942 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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This paper presents an adaptive denoising approach aiming to improve the visibility and detectability of hemorrhage from brain computed tomography (CT) images. The suggested approach fuses the images denoised by total variation (TV) method, denoised by curvelet-based method, and edge information extracted from the noise residue of TV method. The edge information is extracted from the noise residue of TV method by processing it through curvelet transform. The visual interpretation shows that the proposed approach not only reduces the staircase effect caused by total variation method but also reduces visual distortion induced by curvelet transform in the homogeneous areas of the CT images. The denoising abilities of the proposed method are further evaluated by segmenting the hemorrhagic brain area using region-growing method. The sensitivity, specificity, Jaccard index, and Dice coefficients were calculated for different noise levels. The comparative results show that the significant improvement has yielded in the brain hemorrhage detection from CT images after denoising it with the proposed approach. |
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Authors:
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H S Bhadauria; M L Dewal |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-1-25 |
Journal Detail:
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Title: Journal of digital imaging : the official journal of the Society for Computer Applications in Radiology Volume: - ISSN: 1618-727X ISO Abbreviation: - Publication Date: 2012 Jan |
Date Detail:
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Created Date: 2012-1-25 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9100529 Medline TA: J Digit Imaging Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Roorkee-247667, India, hsb76iitr@gmail.com. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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