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Medical Image Understanding and Analysis

22nd Conference, MIUA 2018, Southampton, UK, July 9-11, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Mark Nixon

    1. School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom

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  2. Sasan Mahmoodi

    1. School of Electronics and Computer Science, University of Southampton, Southampton, Southampton, United Kingdom

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  3. Reyer Zwiggelaar

    1. Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 894)

Included in the following conference series:

Conference proceedings info: MIUA 2018.

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About this book

This book constitutes the refereed proceedings of the 22st Annual Conference on Medical Image Understanding and Analysis, MIUA 2018, held in Southampton, UK, in July 2018.The 34 revised full papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on liver analysis, medical image analysis, texture and image analysis, MRI: applications and techniques, segmentation in medical images, CT: learning and planning, ocular imaging analysis, applications of medical image analysis.

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Table of contents (34 papers)

  1. Front Matter

    Pages I-XIV
    Download chapter PDF

  2. Deep Learning in Medical Imaging

    1. Front Matter

      Pages 1-1
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    2. A Multi-resolution Deep Learning Framework for Lung Adenocarcinoma Growth Pattern Classification

      • Najah Alsubaie, Muhammad Shaban, David Snead, Ali Khurram, Nasir Rajpoot
      Pages 3-11

    3. Convolutional Neural Networks for Efficient Localization of Interstitial Lung Disease Patterns in HRCT Images

      • Sunita Agarwala, Abhishek Kumar, Debashis Nandi, Ashis Kumar Dhara, Anup Sadhu, Sumitra Basu Thakur et al.
      Pages 12-22

    4. Segmentating Nucleus Membranes in SBFSEM Volume Data with Deep Neural Networks

      • Yassar Almutairi, Tim Cootes, Karl Kadler
      Pages 23-34

  3. Special Session: Liver Analysis

    1. Front Matter

      Pages 35-35
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    2. Novel Quantitative Magnetic Resonance Imaging Features with Liver Function Tests to Distinguish Parenchymal and Biliary Disease

      • Katherine Arndtz, Benjamin Irving, Peter Eddowes, Dan Green, Matt Kelly, Naomi Jayaratne et al.
      Pages 37-43

    3. Regional Assessment of Liver Disease Progression and Response to Therapy by Multi-time Point m-SLIC Correspondence

      • Benjamin Irving, Chloe Hutton, Katherine Arndtz, Naomi Jayaratne, Matt Kelly, Rajarshi Banerjee et al.
      Pages 44-50

    4. Automated Detection of Cystic Lesions in Quantitative T1 Liver Images

      • Marta Wojciechowska, Benjamin Irving, Andrea Dennis, Henry R. Wilman, Rajarshi Banerjee, Sir Michael Brady et al.
      Pages 51-56

    5. Voxel-Wise Analysis of Paediatric Liver MRI

      • Ged Ridgway, Kamil Janowski, Andrea Dennis, Velicia Bachtiar, John McGonigle, Chris Everitt et al.
      Pages 57-62

  4. Medical Image Analysis

    1. Front Matter

      Pages 63-63
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    2. Quantitative Evaluation of Correction Methods and Simulation of Motion Artifacts for Rotary Pullback Imaging Catheters

      • Elham Abouei, Anthony M. D. Lee, Geoffrey Hohert, Pierre Lane, Stephen Lam, Calum MacAulay
      Pages 65-73

    3. A Voting-Based Encoding Technique for the Classification of Gleason Score for Prostate Cancers

      • Zobia Suhail, Arif Mahmood, Liping Wang, Paul N. Malcolm, Reyer Zwiggelaar
      Pages 74-83

    4. Segmentation of Lung Field in HRCT Images Using U-Net Based Fully Convolutional Networks

      • Abhishek Kumar, Sunita Agarwala, Ashis Kumar Dhara, Debashis Nandi, Sumitra Basu Thakur, Ashok Kumar Bhadra et al.
      Pages 84-93

    5. Identifying Shape-Based Biomarkers for Diagnosis of Parkinson’s Disease from Ioflupane (123I) SPECT Data

      • Vanessa Azzopardi, Matthew Guy, Emma Lewis
      Pages 94-105

    6. Features for the Detection of Flat Polyps in Colonoscopy Video

      • Miao Fan, Jared Vicory, Sarah McGill, Stephen Pizer, Julian Rosenman
      Pages 106-117

    7. Feature Analysis of Biomarker Descriptors for HER2 Classification of Histology Slides

      • Ramakrishnan Mukundan
      Pages 118-129

    8. Analysis of the Symmetry of Electrodes for Electropalatography with Cone Beam CT Scanning

      • Jo Verhoeven, Naomi Rachel Miller, Constantino Carlos Reyes-Aldasoro
      Pages 130-139

  5. Texture and Image Analysis

    1. Front Matter

      Pages 141-141
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    2. Breast Tissue Classification Using Local Binary Pattern Variants: A Comparative Study

      • Minu George, Reyer Zwiggelaar
      Pages 143-152
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Other volumes

  1. Medical Image Understanding and Analysis

Editors and Affiliations

  • School of Electronics and Computer Science, University of Southampton, Southampton, United Kingdom

    Mark Nixon

  • School of Electronics and Computer Science, University of Southampton, Southampton, Southampton, United Kingdom

    Sasan Mahmoodi

  • Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom

    Reyer Zwiggelaar

Bibliographic Information

  • Book Title: Medical Image Understanding and Analysis

  • Book Subtitle: 22nd Conference, MIUA 2018, Southampton, UK, July 9-11, 2018, Proceedings

  • Editors: Mark Nixon, Sasan Mahmoodi, Reyer Zwiggelaar

  • Series Title: Communications in Computer and Information Science

  • DOI: https://doi.org/10.1007/978-3-319-95921-4

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2018

  • Softcover ISBN: 978-3-319-95920-7Published: 21 August 2018

  • eBook ISBN: 978-3-319-95921-4Published: 20 August 2018

  • Series ISSN: 1865-0929

  • Series E-ISSN: 1865-0937

  • Edition Number: 1

  • Number of Pages: XIV, 380

  • Number of Illustrations: 191 b/w illustrations

  • Topics: Image Processing and Computer Vision, Artificial Intelligence

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