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Thoracic Image Analysis = Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Thoracic Image Analysis/ edited by Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Sarah Gerard, Bianca Lassen-Schmidt, Colin Jacobs, Reinhard Beichel, Kensaku Mori.
其他題名:	Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /
其他作者:	Petersen, Jens.
面頁冊數:	X, 166 p. 63 illus., 49 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Optical data processing. -
電子資源:	https://doi.org/10.1007/978-3-030-62469-9
ISBN:	9783030624699

Thoracic Image Analysis = Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /
Thoracic Image AnalysisSecond International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /[electronic resource] :edited by Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Sarah Gerard, Bianca Lassen-Schmidt, Colin Jacobs, Reinhard Beichel, Kensaku Mori. - 1st ed. 2020. - X, 166 p. 63 illus., 49 illus. in color.online resource. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;12502. - Image Processing, Computer Vision, Pattern Recognition, and Graphics ;9219.

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.

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.

ISBN: 9783030624699

Standard No.: 10.1007/978-3-030-62469-9doiSubjects--Topical Terms:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Thoracic Image Analysis = Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /
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