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Title:
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DENOISING APPROACH FOR HIGH-RESOLUTION COMPUTED TOMOGRAPHY DATA |
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Author(s):
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Jakub Salplachta, Tomás Zikmund and Jozef Kaiser |
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ISBN:
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978-989-8533-79-1 |
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Editors:
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Katherine Blashki and Yingcai Xiao |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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CT, High-Resolution Data, Noise Variance Estimation, Noise Reduction |
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Type:
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Poster/Demonstration |
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First Page:
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439 |
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Last Page:
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441 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Noise presence in CT (computed tomography) data distorts acquired information and negatively affects data interpretation, therefore denoising has become important pre-processing step of CT data analysis. Until today many efforts have been done regarding noise reduction in field of low-dose (medical) CT but no complex denoising methodology and noise properties knowledge exist for submicron computed tomography. This poster presents preliminary results of ongoing research regarding noise reduction in submicron CT data. New algorithms for noise properties estimation and noise reduction were proposed and their functionality tested on data from laboratory based system (Rigaku nano3DX machine) equipped with CCD detector. |
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