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
Tanveer Syeda-Mahmood; Xiang Li; Anant Madabhushi; Hayit Greenspan; Quanzheng Li; Richard Leahy; Bin Dong; Hongzhi Wang Springer Nature Switzerland AG (2021) Pehmeäkantinen kirja
Tanveer Syeda-Mahmood; Klaus Drechsler; Hayit Greenspan; Anant Madabhushi; Alexandros Karargyris; Marius George Linguraru Springer Nature Switzerland AG (2020) Pehmeäkantinen kirja
Henning Müller; Tanveer Syeda-Mahmood; James Duncan; Fei Wang; Jayashree Kalpathy-Cramer Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2010) Pehmeäkantinen kirja
Danail Stoyanov; Zeike Taylor; Gustavo Carneiro; Tanveer Syeda-Mahmood; Anne Martel; Lena Maier-Hein; João Manuel Tavares Springer Nature Switzerland AG (2018) Pehmeäkantinen kirja
Kenji Suzuki; Mauricio Reyes; Tanveer Syeda-Mahmood; Ender Konukoglu; Ben Glocker; Roland Wiest; Yaniv Gur; Ha Greenspan Springer Nature Switzerland AG (2019) Pehmeäkantinen kirja
John S. H. Baxter (ed.); Islem Rekik (ed.); Roy Eagleson (ed.); Luping Zhou (ed.); Tanveer Syeda-Mahmood (ed.); Hongz Wang Springer (2022) Pehmeäkantinen kirja
Hayit Greenspan; Anant Madabhushi; Parvin Mousavi; Septimiu Salcudean; James Duncan; Tanveer Syeda-Mahmood; Russel Taylor Springer International Publishing AG (2023) Pehmeäkantinen kirja
Richard Boyle; Bahram Parvin; Darko Koracin; Nikos Paragios; Syeda-Mahmood Tanveer; Tao Ju; Zicheng Liu; Sabi Coquillart Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2007) Pehmeäkantinen kirja
Richard Boyle; Bahram Parvin; Darko Koracin; Nikos Paragios; Syeda-Mahmood Tanveer; Tao Ju; Zicheng Liu; Sabi Coquillart Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2007) 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.