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Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis : 7th Joint International Workshop, CVII-STENT 2018 and Third International Workshop, LABELS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / edited by Danail Stoyanov, Zeike Taylor, Simone Balocco, Raphael Sznitman, Anne Martel, Lena Maier-Hein, Luc Duong, Guillaume Zahnd, Stefanie Demirci, Shadi Albarqouni, Su-Lin Lee, Stefano Moriconi, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, Eric Granger, Pierre Jannin.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11043
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11043
- Language:
- English
- Subjects (All):
- Computer vision.
- Medical informatics.
- Artificial intelligence.
- Computer engineering.
- Computer networks.
- Computer Vision.
- Health Informatics.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Local Subjects:
- Computer Vision.
- Health Informatics.
- Artificial Intelligence.
- Computer Engineering and Networks.
- Physical Description:
- 1 online resource (XVII, 202 pages) : 111 illustrations, 65 illustrations in color.
- Edition:
- 1st ed. 2018.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2018.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed joint proceedings of the 7th Joint International Workshop on Computing and Visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the Third International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 9 full papers presented at CVII-STENT 2017 and the 12 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.
- Contents:
- Blood-flow estimation in the hepatic arteries based on 3D/2D angiography registration
- Automated quantification of blood flow velocity from time-resolved CT angiography
- Multiple device segmentation for fluoroscopic imaging using multi-task learning
- Segmentation of the Aorta Using Active Contours with Histogram-Based Descriptors
- Layer Separation in X-ray Angiograms for Vessel Enhancement with Fully Convolutional Network
- Generation of a HER2 breast cancer gold-standard using supervised learning from multiple experts
- Deep Learning-based Detection and Segmentation for BVS Struts in IVOCT Images
- Towards Automatic Measurement of Type B Aortic Dissection Parameters
- Prediction of FFR from IVUS Images using Machine Learning
- Deep Learning Retinal Vessel Segmentation From a Single Annotated Example: An Application of Cyclic Generative Adversarial Neural Networks
- An Efficient and Comprehensive Labeling Tool for Large-scale Annotation of Fundus Images
- Crowd disagreement about medical images is informative
- Imperfect Segmentation Labels: How Much Do They Matter?
- Crowdsourcing annotation of surgical instruments in videos of cataract surgery
- Four-dimensional ASL MR angiography phantoms with noise learned by neural styling
- Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
- Capsule Networks against Medical Imaging Data Challenges
- Fully Automatic Segmentation of Coronary Arteries based on Deep Neural Network in Intravascular Ultrasound Images
- Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos
- Radiology Objects in COntext (ROCO)
- Improving out-of-sample prediction of quality of MRIQC.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-01364-6
- 9783030013646
- Access Restriction:
- Restricted for use by site license.
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