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Thoracic image analysissecond intern...

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Thoracic image analysissecond international workshop, TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Thoracic image analysisedited by Jens Petersen ... [et al.].
Reminder of title:	second international workshop, TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020 : proceedings /
remainder title:	TIA 2020
other author:	Petersen, Jens.
corporate name:
Published:	Cham :Springer International Publishing :2020.
Description:	x, 166 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	ChestCase studies.Imaging
Online resource:	https://doi.org/10.1007/978-3-030-62469-9
ISBN:	9783030624699$q(electronic bk.)

Thoracic image analysissecond 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] :TIA 2020edited by Jens Petersen ... [et al.]. - Cham :Springer International Publishing :2020. - x, 166 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,125020302-9743 ;. - Lecture notes in computer science ;4891..

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$q(electronic bk.)

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

558867
Chest
--Imaging--Case studies.

LC Class. No.: RC941 / .T53 2020

Dewey Class. No.: 617.540754

Thoracic image analysissecond international workshop, TIA 2020, held in conjunction with MICCAI 2020, Lima, Peru, October 8, 2020 : proceedings /
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520 $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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