Thoracic image analysis : second international workshop, TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings / Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Sarah Gerard, Bianca Lassen-Schmidt, Colin Jacobs, Reinhard Beichel, Kensaku Mori (eds.).
Material type:
TextSeries: Lecture notes in computer science ; 12502. | LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics ; ; 12502.Publisher: Cham, Switzerland : Springer, [2020]Description: 1 online resource (x, 166 pages) : illustrations (some color)Content type: - text
- computer
- online resource
- 9783030624699
- 3030624692
- TIA 2020
- Chest -- Imaging -- Congresses
- Image analysis -- Mathematical models -- Congresses
- Diagnostic imaging -- Data processing -- Congresses
- Optical data processing
- Application software
- Computers
- Artificial intelligence
- Thoracic Cavity -- diagnostic imaging
- Computers
- Artificial Intelligence
- Thorax -- Imagerie -- Congrès
- Analyse d'images -- Modèles mathématiques -- Congrès
- Imagerie pour le diagnostic -- Informatique -- Congrès
- Traitement optique de l'information
- Logiciels d'application
- Ordinateurs
- Intelligence artificielle
- computers
- artificial intelligence
- Image analysis -- Mathematical models
- Diagnostic imaging -- Data processing
- Chest -- Imaging
- Application software
- Artificial intelligence
- Computers
- Optical data processing
- 617.5/40754 23
- RC941
- WF 970
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|
eBook
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e-Library | eBook LNCS | Available |
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.
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.
Includes author index.
Online resource; title from PDF title page (SpringerLink, viewed January 27, 2021).
Includes bibliographical references and index.
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