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ID 114035
タイトル別表記
Texture analysis of myopathy
著者
野寺, 裕之 Tokushima University|Kanazawa Medical University KAKEN研究者をさがす
Sogawa, Kazuki Tokushima University
Takamatsu, Naoko Tokushima University
Hashiguchi, Shuji Tokushima University
Saito, Miho Tokushima Hospital
Mori, Atsuko Tokushima University|Itsuki Hospital
キーワード
myopathy
texture analysis
muscle ultrasound
machine learning
資料タイプ
学術雑誌論文
抄録
Given the recent technological advent of muscle ultrasound (US), classification of various myopathic conditions could be possible, especially by mathematical analysis of muscular fine structure called texture analysis. We prospectively enrolled patients with three neuromuscular conditions and their lower leg US images were quantitatively analyzed by texture analysis and machine learning methodology in the following subjects : Inclusion body myositis (IBM) [N=11] ; myotonic dystrophy type 1 (DM1) [N=19] ; polymyositis/dermatomyositis (PM-DM) [N=21]. Although three-group analysis achieved up to 58.8% accuracy, two-group analysis of IBM plus PM-DM versus DM1 showed 78.4% accuracy. Despite the small number of subjects, texture analysis of muscle US followed by machine learning might be expected to be useful in identifying myopathic conditions.
掲載誌名
The Journal of Medical Investigation
ISSN
13496867
13431420
cat書誌ID
AA12022913
AA11166929
出版者
Tokushima University Faculty of Medicine
66
3-4
開始ページ
237
終了ページ
240
並び順
237
発行日
2019-08
EDB ID
出版社版DOI
出版社版URL
フルテキストファイル
言語
eng
著者版フラグ
出版社版
部局
医学系
病院