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201208 ||| eng |
| 020 |
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|a 9783030624699
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| 100 |
1 |
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|a Petersen, Jens
|e [editor]
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| 245 |
0 |
0 |
|a Thoracic Image Analysis
|h Elektronische Ressource
|b Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings
|c edited by Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Sarah Gerard, Bianca Lassen-Schmidt, Colin Jacobs, Reinhard Beichel, Kensaku Mori
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a X, 166 p. 63 illus., 49 illus. in color
|b online resource
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| 505 |
0 |
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|a Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN -- 3D Deep Convolutional Neural Network-based Ventilated Lung Segmentation using Multi-nuclear Hyperpolarized Gas MRI -- Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet -- 3D Probabilistic Segmentation and Volumetry from 2D Projection Images -- CovidDiagnosis: Deep Diagnosis of Covid-19 Patients using Chest X-rays -- Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification -- A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis -- Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection -- Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation -- MRI to CTA Translation for Pulmonary Artery Evaluation using CycleGANs Trained with Unpaired Data -- Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting -- Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS -- Deep Group-wise Variational Diffeomorphic Image Registration
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| 653 |
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|a Computer vision
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Computer Vision
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| 653 |
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|a Computers
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| 653 |
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|a Application software
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Computing Milieux
|
| 700 |
1 |
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|a San José Estépar, Raúl
|e [editor]
|
| 700 |
1 |
|
|a Schmidt-Richberg, Alexander
|e [editor]
|
| 700 |
1 |
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|a Gerard, Sarah
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-62469-9
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-62469-9?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.37
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| 520 |
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|a This book constitutes the proceedings of the Second International Workshop on Thoracic Image Analysis, TIA 2020, held in Lima, Peru, in October 2020. Due to COVID-19 pandemic the conference was held virtually. COVID-19 infection has brought a lot of attention to lung imaging and the role of CT imaging in the diagnostic workflow of COVID-19 suspects is an important topic. The 14 full papers presented deal with all aspects of image analysis of thoracic data, including: image acquisition and reconstruction, segmentation, registration, quantification, visualization, validation, population-based modeling, biophysical modeling (computational anatomy), deep learning, image analysis in small animals, outcome-based research and novel infectious disease applications
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