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-Reference-Cited by-同舟云学术

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

Published:2017-08-31 Issue:10 Volume:44 Page:5210-5220
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Lavdas Ioannis¹,Glocker Ben²,Kamnitsas Konstantinos²,Rueckert Daniel²,Mair Henrietta³,Sandhu Amandeep⁴,Taylor Stuart A.³,Aboagye Eric O.¹,Rockall Andrea G.⁵

Affiliation:

1. Imperial College Comprehensive Cancer Imaging Centre (C.C.I.C.); Hammersmith Campus, Commonwealth Building Main Office, Ground Floor, Du Cane Road London W12 0NN UK

2. Biomedical Image Analysis Group; Department of Computing; Imperial College London; Huxley Building, 180 Queen's Gate London SW7 2AZ UK

3. Department of Imaging; University College London Hospitals NHS Foundation Trust; Euston Road London NW1 2BU UK

4. Department of Radiology Hammersmith Hospital; Imperial College Healthcare NHS Trust; DuCane Road London W12 0NN UK

5. Department of Radiology; The Royal Marsden NHS Foundation Trust; Fulham Road London SW3 6JJ UK

Funder

National Institute of Health Research

Publisher

Wiley

Subject

General Medicine

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