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Computer-Aided Analysis of Gastrointestinal Videos

  • Book
  • © 2021

Overview

Editors:
  1. Jorge Bernal

    1. Computer Vision Center and Computer Science Department, Autonomous University of Barcelona, Bellaterra, Spain

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  2. Aymeric Histace

    1. ETIS UMR 8051 (CY Paris Cergy University, ENSEA, CNRS), École Nationale Supérieure de l’Electronique et de ses Applications, Cergy, France

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  • Presents the first dedicated volume on computer-aided gastrointestinal video analysis
  • Provides insights from both technical and clinical domains, with a special focus on the clinical applicability of the methods described
  • Describes state-of-the-art research, drawn from challenges organized in conjunction with the MICCAI conference

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Table of contents (24 chapters)

  1. Front Matter

    Pages i-xxiv
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  2. Clinical Context

    1. Front Matter

      Pages 1-1
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    2. Clinical Context for Intelligent Systems in Colonoscopy

      • Gloria Fernández-Esparrach, Ana García-Rodríguez
      Pages 3-8

    3. Clinical Context for Wireless Capsule Endoscopy Image Analysis

      • Romain Leenhardt, Xavier Dray, Aymeric Histace
      Pages 9-13

  3. Technical Context

    1. Front Matter

      Pages 15-15
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    2. Technical Context for Intelligent Systems in Colonoscopy

      • F. Javier Sánchez, Yael Tudela, Marina Riera, Jorge Bernal
      Pages 17-32

    3. Technical Context for Wireless Capsule Endoscopy Image Analysis

      • Aymeric Histace
      Pages 33-37

  4. Methodologies

    1. Front Matter

      Pages 39-39
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    2. Combination of Color-Based Segmentation, Markov Random Fields and Multilayer Perceptron

      • Pedro Miguel Vieira, Nuno Renato Freitas, Carla Rolanda, Carlos Santo Lima
      Pages 41-47

    3. Hand Crafted Method: ROI Selection and Texture Description

      • Orlando Chuquimia, Bertrand Granado, Xavier Dray, Andrea Pinna
      Pages 49-58

    4. AECNN: Adversarial and Enhanced Convolutional Neural Networks

      • Saeed Izadi, Ghassan Hamarneh
      Pages 59-62

    5. Dilated ResFCN and SE-Unet for Polyp Segmentation

      • Yunbo Guo, Bogdan J. Matuszewski
      Pages 63-73

    6. Multi-encoder Decoder Network for Polyp Detection

      • Ahmed Mohammed, Marius Pedersen
      Pages 75-80

    7. Multi-resolution Multi-task Network and Polyp Tracking

      • Hanbo Chen
      Pages 81-89

    8. Region-Based Convolutional Neural Network for Polyp Detection and Segmentation

      • Hemin Ali Qadir, Ilangko Balasingham, Younghak Shin
      Pages 91-98

    9. ResNet

      • Isabel Amaya-Rodriguez, Isabel Amaya-Rodriguez, Javier Civit-Masot, Francisco Luna-Perejon, Lourdes Duran-Lopez, Alexander Rakhlin et al.
      Pages 99-114

    10. Multi-scale Ensemble of ResNet Variants

      • Joost van der Putten, Farhad Ghazvinian Zanjani
      Pages 115-119

    11. Convolutional LSTM

      • Tom Eelbode, Pieter Sinonquel, Raf Bisschops, Frederik Maes
      Pages 121-126

    12. TernausNet

      • Vladimir I. Iglovikov, Alexey A. Shvets
      Pages 127-132

    13. Regression-Based Convolutional Neural Network with a Tracker

      • Ruikai Zhang, Carmen C. Y. Poon
      Pages 133-139
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Keywords

About this book

This book opens with an introduction to the main purpose and tasks of the GIANA challenge, as well as a summary and an analysis of the results and performance obtained by the 20 participating teams. The early and accurate diagnosis of gastrointestinal diseases is critical for increasing the chances of patient survival, and efficient screening is vital for locating precursor lesions. Video colonoscopy and wireless capsule endoscopy (WCE) are the gold-standard tools for colon and intestinal tract screening, respectively. Yet these tools still present some drawbacks, such as lesion miss rate, lack of in vivo diagnosis capabilities, and perforation risk. To mitigate these, computer-aided detection/diagnosis systems can play a key role in assisting clinicians in the different stages of the exploration.

This book presents the latest, state-of-the-art approaches in this field, and also tackles the clinical considerations required to efficiently deploy these systems in the exploration room. The coverage draws upon results from the Gastrointestinal Image Analysis (GIANA) Challenge, part of the EndoVis satellite events of the conferences MICCAI 2017 and 2018. Each method proposed to address the different subtasks of the challenges is detailed in a separate chapter, offering a deep insight into this topic of interest for public health.


This book appeals to researchers, practitioners, and lecturers spanning both the computer vision and gastroenterology communities.

Editors and Affiliations

  • Computer Vision Center and Computer Science Department, Autonomous University of Barcelona, Bellaterra, Spain

    Jorge Bernal

  • ETIS UMR 8051 (CY Paris Cergy University, ENSEA, CNRS), École Nationale Supérieure de l’Electronique et de ses Applications, Cergy, France

    Aymeric Histace

About the editors

Dr. Jorge Bernal del Nozal is Associate Professor in the Department of Computer Science at the Autonomous University of Barcelona, and Associate Researcher in the Computer Vision Center, Barcelona, Spain. 

Dr. Aymeric Histace is Full Professor of Computer Vision in the ETIS (Information Processing and System Team) lab at ENSEA Cergy-Pontoise, France. 

Bibliographic Information

  • Book Title: Computer-Aided Analysis of Gastrointestinal Videos

  • Editors: Jorge Bernal, Aymeric Histace

  • DOI: https://doi.org/10.1007/978-3-030-64340-9

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-64339-3Published: 10 July 2021

  • Softcover ISBN: 978-3-030-64342-3Published: 10 July 2022

  • eBook ISBN: 978-3-030-64340-9Published: 09 July 2021

  • Edition Number: 1

  • Number of Pages: XXIV, 187

  • Number of Illustrations: 13 b/w illustrations, 59 illustrations in colour

  • Topics: Image Processing and Computer Vision, Machine Learning, Imaging / Radiology

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