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ORCIDOR/MLCN@MICCAI 2019: Shenzhen, China
- Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel A. Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang:
OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging - Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings. Lecture Notes in Computer Science 11796, Springer 2019, ISBN 978-3-030-32694-4
Proceedings of the 2nd International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019)
- Abdolrahim Kadkhodamohammadi, Imanol Luengo, Santiago Barbarisi, Hinde Taleb, Evangello Flouty, Danail Stoyanov:
Feature Aggregation Decoder for Segmenting Laparoscopic Scenes. 3-11 - Johannes Fauser, Moritz Fuchs, Ahmed Ghazy, Bernhard Dorweiler, Anirban Mukhopadhyay:
Preoperative Planning for Guidewires Employing Shape-Regularized Segmentation and Optimized Trajectories. 12-20 - V. Vishal, Neeraj Sharma, Munendra Singh
:
Guided Unsupervised Desmoking of Laparoscopic Images Using Cycle-Desmoke. 21-28 - Dominik Rivoir, Sebastian Bodenstedt, Felix von Bechtolsheim, Marius Distler, Jürgen Weitz, Stefanie Speidel:
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration. 29-37 - Leonardo A. Ayala, Sebastian J. Wirkert, Janek Gröhl, Mildred A. Herrera, Adrián Hernández-Aguilera, Anant Suraj Vemuri, Edgar Santos, Lena Maier-Hein:
Live Monitoring of Haemodynamic Changes with Multispectral Image Analysis. 38-46 - Chin-Boon Chng, Pooi-Mun Wong, Nicholas J. H. Ho, Xiaoyu Tan, Chee-Kong Chui:
Towards a Cyber-Physical Systems Based Operating Room of the Future. 47-55
Proceedings of the 2nd International Workshop on Machine Learning in Clinical Neuroimaging: Entering the Era of Big Data via Transfer Learning and Data Harmonization (MLCN 2019)
- Armin W. Thomas, Klaus-Robert Müller, Wojciech Samek:
Deep Transfer Learning for Whole-Brain FMRI Analyses. 59-67 - Mauricio Orbes-Arteaga, M. Jorge Cardoso, Lauge Sørensen, Christian Igel, Sébastien Ourselin, Marc Modat, Mads Nielsen, Akshay Pai:
Knowledge Distillation for Semi-supervised Domain Adaptation. 68-76 - Maria Inês Meyer, Ezequiel de la Rosa, Koen Van Leemput, Diana Maria Sima:
Relevance Vector Machines for Harmonization of MRI Brain Volumes Using Image Descriptors. 77-85 - Annika Hänsch, Bastian Cheng, Benedikt Frey, Carola Mayer, Marvin Petersen, Iris Lettow, Farhad Yazdan Shenas, Götz Thomalla, Jan Klein, Horst K. Hahn:
Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation. 86-94 - Ahmed El Gazzar, Mirjam Quaak, Leonardo Cerliani, Peter Bloem, Guido van Wingen, Rajat Mani Thomas:
A Hybrid 3DCNN and 3DC-LSTM Based Model for 4D Spatio-Temporal fMRI Data: An ABIDE Autism Classification Study. 95-102 - Florian Dubost, Max Dünnwald, Denver Huff, Vincent Scheumann, Frank Schreiber, Meike W. Vernooij, Wiro J. Niessen, Martin Skalej, Stefanie Schreiber, Steffen Oeltze-Jafra, Marleen de Bruijne:
Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI Across Sites. 103-111
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