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
Herausgegeben:Stoyanov, Danail; Taylor, Zeike; Balocco, Simone; Sznitman, Raphael; Martel, Anne; Maier-Hein, Lena; Duong, Luc; Zahnd, Guillaume; Demirci, Stefanie

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Computer Science 11043
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-030-01363-9
• 1st ed. 2018
• Seitenzahl: 220
• Erscheinungstermin: 17. Oktober 2018
• Englisch
• Abmessung: 235mm x 155mm x 13mm
• Gewicht: 342g
• ISBN-13: 9783030013639
• ISBN-10: 3030013634
• Artikelnr.: 53643195

Inhaltsangabe

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.