Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Anne L. Martel (ed.); Purang Abolmaesumi (ed.); Danail Stoyanov (ed.); Diana Mateus (ed.); Maria A. Zuluaga (ed.); S. Zhou Springer (2020) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Springer Sivumäärä: 166 sivua Asu: Pehmeäkantinen kirja Julkaisuvuosi: 2017, 08.09.2017 (lisätietoa) Kieli: Englanti
This book constitutes the refereed joint proceedings of the 6th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017, and the Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 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 6 full papers presented at CVII-STENT 2017 and the 11 full papers presented at LABELS 2017 were carefully reviewed and selected. The CVII-STENT papers feature the state of the art in imaging, treatment, and computer-assisted intervention in the field of endovascular interventions. The LABELS papers present a variety of approaches for dealing with few labels, from transfer learning to crowdsourcing.
