文献
J-GLOBAL ID:201702268990418695
整理番号:17A1176608
正確な脳病変セグメンテーションのための完全に連結したCRFを用いた効率的なマルチスケール3次元CNN【Powered by NICT】
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
著者 (10件):
Kamnitsas Konstantinos
(Biomedical Image Analysis Group, Imperial College London, UK)
,
Ledig Christian
(Biomedical Image Analysis Group, Imperial College London, UK)
,
Newcombe Virginia F.J.
(University Division of Anaesthesia, Department of Medicine, Cambridge University, UK)
,
Newcombe Virginia F.J.
(Wolfson Brain Imaging Centre, Cambridge University, UK)
,
Simpson Joanna P.
(University Division of Anaesthesia, Department of Medicine, Cambridge University, UK)
,
Kane Andrew D.
(University Division of Anaesthesia, Department of Medicine, Cambridge University, UK)
,
Menon David K.
(University Division of Anaesthesia, Department of Medicine, Cambridge University, UK)
,
Menon David K.
(Wolfson Brain Imaging Centre, Cambridge University, UK)
,
Rueckert Daniel
(Biomedical Image Analysis Group, Imperial College London, UK)
,
Glocker Ben
(Biomedical Image Analysis Group, Imperial College London, UK)
資料名:
Medical Image Analysis
(Medical Image Analysis)
巻:
36
ページ:
61-78
発行年:
2017年
JST資料番号:
W3156A
ISSN:
1361-8415
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)