M. Jorge Cardoso; Tal Arbel; Gustavo Carneiro; Tanveer Syeda-Mahmood; Joao Manuel R. S. Tavares; Mehdi Moradi; An Bradley Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; Su-Lin Lee; Veronika Cheplygina; Simone Balocco; Diana Mateus; Guillaume Zahnd; Maier-Hein Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; Andrew Melbourne; Hrvoje Bogunovic; Pim Moeskops; Xinjian Chen; Ernst Schwartz; Mona Garvin Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; Fei Gao; Bernhard Kainz; Theo Van Walsum; Kuangyu Shi; Kanwal K. Bhatia; Roman Peter; Verca Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; João Manuel R.S. Tavares; Stephen Aylward; Shuo Li; Emad Boctor; Gabor Fichtinger; K Cleary Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; Xiongbiao Luo; Stefan Wesarg; Tobias Reichl; Miguel Ángel González Ballester; Jonatha McLeod Springer International Publishing AG (2017) Pehmeäkantinen kirja
M. Jorge Cardoso; Tal Arbel; Enzo Ferrante; Xavier Pennec; Adrian Dalca; Sarah Parisot; Sarang Joshi; Nema Batmanghelich Springer International Publishing AG (2017) Pehmeäkantinen kirja
Henning Müller; B. Michael Kelm; Tal Arbel; Weidong Cai; M. Jorge Cardoso; Georg Langs; Bjoern Menze; Dimitris Metaxas Springer International Publishing AG (2017) Pehmeäkantinen kirja
Qian Wang; Fausto Milletari; Hien V. Nguyen; Shadi Albarqouni; M. Jorge Cardoso; Nicola Rieke; Ziyue Xu; Konst Kamnitsas Springer Nature Switzerland AG (2019) Pehmeäkantinen kirja
Cristina Oyarzun Laura; M. Jorge Cardoso; Michal Rosen-Zvi; Georgios Kaissis; Marius George Linguraru; Raj Shekhar; Wesarg Springer Nature Switzerland AG (2021) Pehmeäkantinen kirja
Lisa Koch (ed.); M. Jorge Cardoso (ed.); Enzo Ferrante (ed.); Konstantinos Kamnitsas (ed.); Mobarakol Islam (ed.); M Jiang Springer (2023) Pehmeäkantinen kirja
This book constitutes the refereed joint proceedings of the Third International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2017, and the 6th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017.
The 38 full papers presented at DLMIA 2017 and the 5 full papers presented at ML-CDS 2017 were carefully reviewed and selected. The DLMIA papers focus on the design and use of deep learning methods in medical imaging. The ML-CDS papers discuss new techniques of multimodal mining/retrieval and their use in clinical decision support.
