Fully automatic, multiorgan segmentation in normal whole body magnetic resonance imaging (MRI), using classification forests (CFs), convolutional neural networks (CNNs), and a multi-atlas (MA) approach

著录项

• 来源
  《Medical Physics》 |2017年第10期|共11页
• 作者

  Lavdas Ioannis; Glocker Ben; Kamnitsas Konstantinos; Rueckert Daniel; Mair Henrietta; Sandhu Amandeep; Taylor Stuart A.; Aboagye Eric O.; Rockall Andrea G.;

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• 作者单位

  Imperial Coll Comprehens Canc Imaging Ctr CCIC Hammersmith Campus Commonwealth Bldg Main Off;

  Imperial Coll London Dept Comp Biomed Image Anal Grp Huxley Bldg 180 Queens Gate London SW7 2AZ;

  Imperial Coll London Dept Comp Biomed Image Anal Grp Huxley Bldg 180 Queens Gate London SW7 2AZ;

  Imperial Coll London Dept Comp Biomed Image Anal Grp Huxley Bldg 180 Queens Gate London SW7 2AZ;

  Univ Coll London Hosp NHS Fdn Trust Dept Imaging Euston Rd London NW1 2BU England;

  Imperial Coll Healthcare NHS Trust Hammersmith Hosp Dept Radiol DuCane Rd London W12 0NN;

  Univ Coll London Hosp NHS Fdn Trust Dept Imaging Euston Rd London NW1 2BU England;

  Imperial Coll Comprehens Canc Imaging Ctr CCIC Hammersmith Campus Commonwealth Bldg Main Off;

  Royal Marsden NHS Fdn Trust Dept Radiol Fulham Rd London SW3 6JJ England;

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• 收录信息
• 原文格式 PDF
• 正文语种 eng
• 中图分类 基础医学;
• 关键词

  classification forests; convolutional neural networks; fully automatic segmentation; multi-atlas segmentation; whole body MRI;

  机译：分类森林;卷积神经网络;全自动分割;多阿特拉斯分割;全身MRI;