Study of texture analysis on amyloid imaging in positron emission tomography

碩士 === 長庚大學 === 醫學影像暨放射科學系 === 102 === 18F-AV-45 is novel PET tracer for imaging the deposition of amyloid in Alzheimer's disease (AD). The amyloid PET SUVR images are widely applied for AD diagnosis. However, it is difficult to differentiate normal control and mild cognitive impairment signifi...

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Main Authors: Ming Je Tsai, 蔡佲哲
Other Authors: I. T. Hsiao
Format: Others
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/00802699727989343120
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spelling ndltd-TW-102CGU057700052015-10-14T00:18:19Z http://ndltd.ncl.edu.tw/handle/00802699727989343120 Study of texture analysis on amyloid imaging in positron emission tomography 應用紋理分析於類澱粉蛋白沉積正子影像之研究 Ming Je Tsai 蔡佲哲 碩士 長庚大學 醫學影像暨放射科學系 102 18F-AV-45 is novel PET tracer for imaging the deposition of amyloid in Alzheimer's disease (AD). The amyloid PET SUVR images are widely applied for AD diagnosis. However, it is difficult to differentiate normal control and mild cognitive impairment significantly and has less ability of early diagnosis. This study utilized texture analysis which had been applied for different modality images in previous literature for the purpose of improving the shortage of SUVR images. We used phantom study to validate characteristics of feature calculation and evaluated the best texture properties of clinical amyloid imaging study. Aim of this study is to figure out the textural characteristic which can provide local information of the 18F-AV-45 labeled images between different severity trials and may be possibly provide more classification power of disease stages. The results demonstrated that the features obtained from texture analysis can provide local information of amyloid images, and enhanced the diagnosis differentiation ability in AD. As the results, texture analysis is an effective method for increasing extra information from image and aid the disease classification ability for medical images. I. T. Hsiao 蕭穎聰 2014 學位論文 ; thesis 81
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description 碩士 === 長庚大學 === 醫學影像暨放射科學系 === 102 === 18F-AV-45 is novel PET tracer for imaging the deposition of amyloid in Alzheimer's disease (AD). The amyloid PET SUVR images are widely applied for AD diagnosis. However, it is difficult to differentiate normal control and mild cognitive impairment significantly and has less ability of early diagnosis. This study utilized texture analysis which had been applied for different modality images in previous literature for the purpose of improving the shortage of SUVR images. We used phantom study to validate characteristics of feature calculation and evaluated the best texture properties of clinical amyloid imaging study. Aim of this study is to figure out the textural characteristic which can provide local information of the 18F-AV-45 labeled images between different severity trials and may be possibly provide more classification power of disease stages. The results demonstrated that the features obtained from texture analysis can provide local information of amyloid images, and enhanced the diagnosis differentiation ability in AD. As the results, texture analysis is an effective method for increasing extra information from image and aid the disease classification ability for medical images.
author2 I. T. Hsiao
author_facet I. T. Hsiao
Ming Je Tsai
蔡佲哲
author Ming Je Tsai
蔡佲哲
spellingShingle Ming Je Tsai
蔡佲哲
Study of texture analysis on amyloid imaging in positron emission tomography
author_sort Ming Je Tsai
title Study of texture analysis on amyloid imaging in positron emission tomography
title_short Study of texture analysis on amyloid imaging in positron emission tomography
title_full Study of texture analysis on amyloid imaging in positron emission tomography
title_fullStr Study of texture analysis on amyloid imaging in positron emission tomography
title_full_unstemmed Study of texture analysis on amyloid imaging in positron emission tomography
title_sort study of texture analysis on amyloid imaging in positron emission tomography
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/00802699727989343120
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