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CVII-STENT/LABELS@MICCAI 2017: Quebec City, QC, Canada
- M. Jorge Cardoso, Tal Arbel, Su-Lin Lee, Veronika Cheplygina, Simone Balocco, Diana Mateus, Guillaume Zahnd, Lena Maier-Hein, Stefanie Demirci, Eric Granger, Luc Duong, Marc-André Carbonneau, Shadi Albarqouni, Gustavo Carneiro:
Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis - 6th Joint International Workshops, CVII-STENT 2017 and Second International Workshop, LABELS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10-14, 2017, Proceedings. Lecture Notes in Computer Science 10552, Springer 2017, ISBN 978-3-319-67533-6
6th Joint International Workshops on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2017
- Luis Álvarez, Esther González, Julio Esclarín, Luis Gómez, Miguel Alemán-Flores, Agustín Trujillo, Carmelo Cuenca, Luis Mazorra, Pablo G. Tahoces, José M. Carreira:
Robust Detection of Circles in the Vessel Contours and Application to Local Probability Density Estimation. 3-11 - Simone Balocco, Francesco Ciompi, Juan Rigla, Xavier Carrillo, Josepa Mauri, Petia Radeva:
Intra-coronary Stent Localization in Intravascular Ultrasound Sequences, A Preliminary Study. 12-19 - Rosalie Plantefève, Samuel Kadoury, An Tang, Igor Peterlík:
Robust Automatic Graph-Based Skeletonization of Hepatic Vascular Trees. 20-28 - Karen López-Linares, Luis Kabongo, Nerea Lete, Gregory Maclair, Mario Ceresa, Ainhoa García-Familiar, Iván Macía, Miguel Ángel González Ballester:
DCNN-Based Automatic Segmentation and Quantification of Aortic Thrombus Volume: Influence of the Training Approach. 29-38 - Renzo Phellan, Alan Peixinho, Alexandre X. Falcão, Nils Daniel Forkert:
Vascular Segmentation in TOF MRA Images of the Brain Using a Deep Convolutional Neural Network. 39-46 - Ketan Bacchuwar, Jean Cousty, Régis Vaillant, Laurent Najman:
VOIDD: Automatic Vessel-of-Intervention Dynamic Detection in PCI Procedures. 47-56
Second International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2017
- Veronika Cheplygina, Pim Moeskops, Mitko Veta, Behdad Dashtbozorg, Josien P. W. Pluim:
Exploring the Similarity of Medical Imaging Classification Problems. 59-66 - Chuanhai Zhang, Wallapak Tavanapong, Johnny Wong, Piet C. de Groen, Jung-Hwan Oh:
Real Data Augmentation for Medical Image Classification. 67-76 - Joseph G. Jacobs, Gabriel J. Brostow, Alex Freeman, Daniel C. Alexander, Eleftheria Panagiotaki:
Detecting and Classifying Nuclei on a Budget. 77-86 - Yaniv Gur, Mehdi Moradi, Hakan Bulu, Yufan Guo, Colin B. Compas, Tanveer F. Syeda-Mahmood:
Towards an Efficient Way of Building Annotated Medical Image Collections for Big Data Studies. 87-95 - Alison Q. O'Neil, John T. Murchison, Edwin J. R. van Beek, Keith A. Goatman:
Crowdsourcing Labels for Pathological Patterns in CT Lung Scans: Can Non-experts Contribute Expert-Quality Ground Truth? 96-105 - Laurent Lejeune, Mario Christoudias, Raphael Sznitman:
Expected Exponential Loss for Gaze-Based Video and Volume Ground Truth Annotation. 106-115 - Mian Huang, Ghassan Hamarneh:
SwifTree: Interactive Extraction of 3D Trees Supporting Gaming and Crowdsourcing. 116-125 - Silas Nyboe Ørting, Veronika Cheplygina, Jens Petersen, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne:
Crowdsourced Emphysema Assessment. 126-135 - Nicholas Heller, Panagiotis Stanitsas, Vassilios Morellas, Nikolaos Papanikolopoulos:
A Web-Based Platform for Distributed Annotation of Computerized Tomography Scans. 136-145 - Sebastian Otálora, Oscar J. Perdomo, Fabio A. González, Henning Müller:
Training Deep Convolutional Neural Networks with Active Learning for Exudate Classification in Eye Fundus Images. 146-154 - Aïcha BenTaieb, Ghassan Hamarneh:
Uncertainty Driven Multi-loss Fully Convolutional Networks for Histopathology. 155-163
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