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Thoracic Image Analysis

Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Jens Petersen

    1. University of Copenhagen, Copenhagen, Denmark

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  2. Raúl San José Estépar

    1. Harvard Medical School, Boston, USA

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  3. Alexander Schmidt-Richberg

    1. Philips (Germany), Hamburg, Germany

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  4. Sarah Gerard

    1. Harvard Medical School, Boston, USA

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  5. Bianca Lassen-Schmidt

    1. Fraunhofer Institute for Medical Image Computing, Bremen, Germany

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  6. Colin Jacobs

    1. Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands

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  7. Reinhard Beichel

    1. University of Iowa, Iowa City, USA

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  8. Kensaku Mori

    1. Graduate School of Informatics, Nagoya University, Nagoya, Japan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12502)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: TIA 2020.

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Table of contents (14 papers)

  1. Front Matter

    Pages i-x
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  2. Image Segmentation

    1. Front Matter

      Pages 1-1
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    2. Two-Stage Mapping-Segmentation Framework for Delineating COVID-19 Infections from Heterogeneous CT Images

      • Tong Li, Zhuochen Wang, Yanbo Chen, Lichi Zhang, Yaozong Gao, Feng Shi et al.
      Pages 3-13

    3. Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN

      • Rafael Moreta-Martínez, Gonzalo Vegas Sánchez-Ferrero, Lasse Andresen, Jakob Qvortrup Holsting, Raúl San José Estépar
      Pages 14-23

    4. 3D Deep Convolutional Neural Network-Based Ventilated Lung Segmentation Using Multi-nuclear Hyperpolarized Gas MRI

      • Joshua R. Astley, Alberto M. Biancardi, Paul J. C. Hughes, Laurie J. Smith, Helen Marshall, James Eaden et al.
      Pages 24-35

    5. Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet

      • Uday Kamal, Abdul Muntakim Rafi, Rakibul Hoque, Jonathan Wu, Md. Kamrul Hasan
      Pages 36-47

    6. 3D Probabilistic Segmentation and Volumetry from 2D Projection Images

      • Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz
      Pages 48-57

  3. Computer-Aided Diagnosis and Localization

    1. Front Matter

      Pages 59-59
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    2. CovidDiagnosis: Deep Diagnosis of COVID-19 Patients Using Chest X-Rays

      • Kushagra Mahajan, Monika Sharma, Lovekesh Vig, Rishab Khincha, Soundarya Krishnan, Adithya Niranjan et al.
      Pages 61-73

    3. Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification

      • Eduardo H. P. Pooch, Pedro Ballester, Rodrigo C. Barros
      Pages 74-83

    4. A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis

      • Ophir Gozes, Maayan Frid-Adar, Nimrod Sagie, Asher Kabakovitch, Dor Amran, Rula Amer et al.
      Pages 84-93

    5. Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection

      • Marina Codari, Antonio Pepe, Gabriel Mistelbauer, Domenico Mastrodicasa, Shannon Walters, Martin J. Willemink et al.
      Pages 94-105

  4. Image Translation and Inpainting

    1. Front Matter

      Pages 107-107
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    2. Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation

      • Pietro Nardelli, Rubén San José Estépar, Farbod N. Rahaghi, Raúl San José Estépar
      Pages 109-117

    3. MRI to CTA Translation for Pulmonary Artery Evaluation Using CycleGANs Trained with Unpaired Data

      • Maialen Stephens, Raúl San José Estepar, Jesús Ruiz-Cabello, Ignacio Arganda-Carreras, Iván Macía, Karen López-Linares
      Pages 118-129

    4. Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting

      • Antonio Pepe, Gabriel Mistelbauer, Christina Gsaxner, Jianning Li, Dominik Fleischmann, Dieter Schmalstieg et al.
      Pages 130-140

  5. Image Registration

    1. Front Matter

      Pages 141-141
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    2. Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS

      • Muhammad F. A. Chaudhary, Yue Pan, Di Wang, Sandeep Bodduluri, Surya P. Bhatt, Alejandro P. Comellas et al.
      Pages 143-154

    3. Deep Group-Wise Variational Diffeomorphic Image Registration

      • Tycho F. A. van der Ouderaa, Ivana Išgum, Wouter B. Veldhuis, Bob D. de Vos
      Pages 155-164

  6. Back Matter

    Pages 165-166
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Other volumes

  1. Thoracic Image Analysis

Keywords

About this book

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.

Editors and Affiliations

  • University of Copenhagen, Copenhagen, Denmark

    Jens Petersen

  • Harvard Medical School, Boston, USA

    Raúl San José Estépar, Sarah Gerard

  • Philips (Germany), Hamburg, Germany

    Alexander Schmidt-Richberg

  • Fraunhofer Institute for Medical Image Computing, Bremen, Germany

    Bianca Lassen-Schmidt

  • Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands

    Colin Jacobs

  • University of Iowa, Iowa City, USA

    Reinhard Beichel

  • Graduate School of Informatics, Nagoya University, Nagoya, Japan

    Kensaku Mori

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