Abstract is missing.
- Blood-Flow Estimation in the Hepatic Arteries Based on 3D/2D Angiography RegistrationSimon Lessard, Rosalie Plantefève, François Michaud, Catherine Huet, Gilles Soulez, Samuel Kadoury. 3-10 [doi]
- Automated Quantification of Blood Flow Velocity from Time-Resolved CT AngiographyPieter Thomas Boonen, Nico Buls, Gert Van Gompel, Yannick De Brucker, Dimitri Aerden, Johan de Mey, Jef Vandemeulebroucke. 11-18 [doi]
- Multiple Device Segmentation for Fluoroscopic Imaging Using Multi-task LearningKatharina Breininger, Tobias Würfl, Tanja Kurzendorfer, Shadi Albarqouni, Marcus Pfister, Markus Kowarschik, Nassir Navab, Andreas K. Maier. 19-27 [doi]
- Segmentation of the Aorta Using Active Contours with Histogram-Based DescriptorsMiguel Alemán-Flores, Daniel Santana-Cedrés, Luis Álvarez, Agustín Trujillo, Luis Gómez, Pablo G. Tahoces, José M. Carreira. 28-35 [doi]
- Layer Separation in X-ray Angiograms for Vessel Enhancement with Fully Convolutional NetworkHaidong Hao, Hua Ma, Theo van Walsum. 36-44 [doi]
- Generation of a HER2 Breast Cancer Gold-Standard Using Supervised Learning from Multiple ExpertsVioleta Chang. 45-54 [doi]
- Deep Learning-Based Detection and Segmentation for BVS Struts in IVOCT ImagesYihui Cao, Yifeng Lu, Qinhua Jin, Jing Jing, Yundai Chen, Jianan Li, Rui Zhu 0005. 55-63 [doi]
- Towards Automatic Measurement of Type B Aortic Dissection Parameters: Methods, Applications and PerspectiveJianning Li, Long Cao, Cheng W, Bowen M. 64-72 [doi]
- Prediction of FFR from IVUS Images Using Machine LearningGeena Kim, June Goo Lee, Soo-Jin Kang, Paul Ngyuen, Do-Yoon Kang, Pil Hyung Lee, Jung-Min Ahn, Duk-Woo Park, Seung-Whan Lee, Young-Hak Kim, Cheol Whan Lee, Seong-Wook Park, Seung-Jung Park. 73-81 [doi]
- Deep Learning Retinal Vessel Segmentation from a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural NetworksPraneeth Sadda, John A. Onofrey, Xenophon Papademetris. 82-91 [doi]
- An Efficient and Comprehensive Labeling Tool for Large-Scale Annotation of Fundus ImagesJaemin Son, Sangkeun Kim, Sang-Jun Park, Kyu-Hwan Jung. 95-104 [doi]
- Crowd Disagreement About Medical Images Is InformativeVeronika Cheplygina, Josien P. W. Pluim. 105-111 [doi]
- Imperfect Segmentation Labels: How Much Do They Matter?Nicholas Heller, Joshua Dean, Nikolaos Papanikolopoulos. 112-120 [doi]
- Crowdsourcing Annotation of Surgical Instruments in Videos of Cataract SurgeryTae-Soo Kim, Anand Malpani, Austin Reiter, Gregory D. Hager, Shameema Sikder, S. Swaroop Vedula. 121-130 [doi]
- Four-Dimensional ASL MR Angiography Phantoms with Noise Learned by Neural StylingRenzo Phellan, Thomas Lindner 0002, Michael Helle, Thiago Vallin Spina, Alexandre X. Falcão, Nils Daniel Forkert. 131-139 [doi]
- Feature Learning Based on Visual Similarity Triplets in Medical Image Analysis: A Case Study of Emphysema in Chest CT ScansSilas Nyboe Ørting, Jens Petersen, Veronika Cheplygina, Laura H. Thomsen, Mathilde M. W. Wille, Marleen de Bruijne. 140-149 [doi]
- Capsule Networks Against Medical Imaging Data ChallengesAmelia Jiménez-Sánchez, Shadi Albarqouni, Diana Mateus. 150-160 [doi]
- Fully Automatic Segmentation of Coronary Arteries Based on Deep Neural Network in Intravascular Ultrasound ImagesSekeun Kim, Yeonggul Jang, Byunghwan Jeon, Youngtaek Hong, Hackjoon Shim, Hyuk-Jae Chang. 161-168 [doi]
- Weakly-Supervised Learning for Tool Localization in Laparoscopic VideosArmine Vardazaryan, Didier Mutter, Jacques Marescaux, Nicolas Padoy. 169-179 [doi]
- Radiology Objects in COntext (ROCO): A Multimodal Image DatasetObioma Pelka, Sven Koitka, Johannes Rückert, Felix Nensa, Christoph M. Friedrich. 180-189 [doi]
- Improving Out-of-Sample Prediction of Quality of MRIQCOscar Esteban, Russell A. Poldrack, Krzysztof J. Gorgolewski. 190-199 [doi]