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1st UNSURE/8th CLIP@MICCAI 2019: Shenzhen, China
- Hayit Greenspan, Ryutaro Tanno, Marius Erdt, Tal Arbel, Christian F. Baumgartner, Adrian V. Dalca, Carole H. Sudre, William M. Wells III, Klaus Drechsler, Marius George Linguraru, Cristina Oyarzun Laura, Raj Shekhar, Stefan Wesarg, Miguel Ángel González Ballester:
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures - First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11840, Springer 2019, ISBN 978-3-030-32688-3
UNSURE 2019: Uncertainty Quantification and Noise Modelling
- Dennis Madsen, Thomas Vetter, Marcel Lüthi:
Probabilistic Surface Reconstruction with Unknown Correspondence. 3-11 - Alireza Sedghi, Tina Kapur, Jie Luo, Parvin Mousavi, William M. Wells III:
Probabilistic Image Registration via Deep Multi-class Classification: Characterizing Uncertainty. 12-22 - Raghav Mehta, Thomas Christinck, Tanya Nair, Paul Lemaître, Douglas L. Arnold, Tal Arbel:
Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference. 23-32 - Gregor N. Ramien, Paul F. Jaeger, Simon A. A. Kohl, Klaus H. Maier-Hein:
Reg R-CNN: Lesion Detection and Grading Under Noisy Labels. 33-41 - Mikael Agn, Koen Van Leemput
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Fast Nonparametric Mutual-Information-based Registration and Uncertainty Estimation. 42-51 - Pieter Van Molle, Tim Verbelen
Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification. 52-61
UNSURE 2019: Domain Shift Robustness
- Min Zhang, Kevin H. Leung, Zili Ma, Jin Wen, Gopal Avinash:
A Generalized Approach to Determine Confident Samples for Deep Neural Networks on Unseen Data. 65-74 - Tim J. Adler
Out of Distribution Detection for Intra-operative Functional Imaging. 75-82
CLIP 2019
- Peifang Guo:
A Clinical Measuring Platform for Building the Bridge Across the Quantification of Pathological N-Cells in Medical Imaging for Studies of Disease. 85-93 - Aoi Shinjo
Spatiotemporal Statistical Model of Anatomical Landmarks on a Human Embryonic Brain. 94-103 - Hirohisa Oda, Kohei Nishio, Takayuki Kitasaka, Benjamin Villard
Spaciousness Filters for Non-contrast CT Volume Segmentation of the Intestine Region for Emergency Ileus Diagnosis. 104-114 - Ayushi Sinha, Xingtong Liu
Recovering Physiological Changes in Nasal Anatomy with Confidence Estimates. 115-124 - Luise Middel, Christoph Palm
Synthesis of Medical Images Using GANs. 125-134 - Shuting Liu, Baochang Zhang
DPANet: A Novel Network Based on Dense Pyramid Feature Extractor and Dual Correlation Analysis Attention Modules for Colon Glands Segmentation. 135-145 - Shi Yin, Qinmu Peng, Hongming Li, Zhengqiang Zhang, Xinge You, Hangfan Liu
Multi-instance Deep Learning with Graph Convolutional Neural Networks for Diagnosis of Kidney Diseases Using Ultrasound Imaging. 146-154 - Debora Gil, Antonio Esteban-Lansaque, Sebastian Stefaniga
Data Augmentation from Sketch. 155-162 - Ruobing Huang, Michael Suttie, J. Alison Noble
An Automated CNN-based 3D Anatomical Landmark Detection Method to Facilitate Surface-Based 3D Facial Shape Analysis. 163-171 - Baochang Zhang
A Device-Independent Novel Statistical Modeling for Cerebral TOF-MRA Data Segmentation. 172-181 - Liyun Tu, Antonio R. Porras
Three-Dimensional Face Reconstruction from Uncalibrated Photographs: Application to Early Detection of Genetic Syndromes. 182-189
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