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Information Processing in Medical Imaging

26th International Conference, IPMI 2019, Hong Kong, China, June 2–7, 2019, Proceedings

  • Albert C. S. Chung
  • James C. Gee
  • Paul A. Yushkevich
  • Siqi Bao
Conference proceedings IPMI 2019

Part of the Lecture Notes in Computer Science book series (LNCS, volume 11492)

Also part of the Image Processing, Computer Vision, Pattern Recognition, and Graphics book sub series (LNIP, volume 11492)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Segmentation

    1. Front Matter
      Pages 1-1
    2. James R. Clough, Ilkay Oksuz, Nicholas Byrne, Julia A. Schnabel, Andrew P. King
      Pages 16-28
    3. Krishna Chaitanya, Neerav Karani, Christian F. Baumgartner, Anton Becker, Olivio Donati, Ender Konukoglu
      Pages 29-41
  3. Classification and Inference

    1. Front Matter
      Pages 43-43
    2. Laurent Chauvin, Kuldeep Kumar, Christian Desrosiers, Jacques De Guise, William Wells III, Matthew Toews
      Pages 45-56
    3. Sara Garbarino, Marco Lorenzi, for the Alzheimer’s Disease Neuroimaging Initiative
      Pages 57-69
  4. Deep Learning

    1. Front Matter
      Pages 71-71
    2. Anees Kazi, Shayan Shekarforoush, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Karsten Kortüm et al.
      Pages 73-85
    3. Karthik Gopinath, Christian Desrosiers, Herve Lombaert
      Pages 86-98
    4. Yunyang Xiong, Hyunwoo J. Kim, Bhargav Tangirala, Ronak Mehta, Sterling C. Johnson, Vikas Singh
      Pages 99-111
    5. Rudrasis Chakraborty, Jose Bouza, Jonathan Manton, Baba C. Vemuri
      Pages 112-124
  5. Reconstruction

    1. Front Matter
      Pages 139-139
    2. Sandesh Ghimire, Prashnna Kumar Gyawali, Jwala Dhamala, John L. Sapp, Milan Horacek, Linwei Wang
      Pages 153-166
  6. Disease Modeling

    1. Front Matter
      Pages 167-167
    2. Vikram Venkatraghavan, Florian Dubost, Esther E. Bron, Wiro J. Niessen, Marleen de Bruijne, Stefan Klein et al.
      Pages 169-180
  7. Shape

    1. Front Matter
      Pages 181-181
    2. Babak Samari, Tabish A. Syed, Kaleem Siddiqi
      Pages 183-194
    3. Alexandre Bône, Maxime Louis, Olivier Colliot, Stanley Durrleman, the Alzheimer’s Disease Neuroimaging Initiative
      Pages 195-207
    4. Paul A. Yushkevich, Ahmed Aly, Jiancong Wang, Long Xie, Robert C. Gorman, Laurent Younes et al.
      Pages 208-220
    5. Loïc Le Folgoc, Daniel C. Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker et al.
      Pages 221-234
  8. Registration

    1. Front Matter
      Pages 235-235
    2. T. Bazeille, H. Richard, H. Janati, B. Thirion
      Pages 237-248
    3. Chen Qin, Bibo Shi, Rui Liao, Tommaso Mansi, Daniel Rueckert, Ali Kamen
      Pages 249-261
  9. Learning Motion

    1. Front Matter
      Pages 263-263
    2. Markus D. Foote, Blake E. Zimmerman, Amit Sawant, Sarang C. Joshi
      Pages 265-276
    3. Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen
      Pages 277-288
  10. Functional Imaging

  11. White Matter Imaging

    1. Front Matter
      Pages 317-317
    2. Ye Wu, Weili Lin, Dinggang Shen, Pew-Thian Yap, and the UNC/UMN Baby Connectome Project Consortium
      Pages 319-331
  12. Posters

    1. Front Matter
      Pages 345-345
    2. Elena Balashova, Jiangping Wang, Vivek Singh, Bogdan Georgescu, Brian Teixeira, Ankur Kapoor
      Pages 347-359
    3. Wouter M. Kouw, Silas N. Ørting, Jens Petersen, Kim S. Pedersen, Marleen de Bruijne
      Pages 360-371
    4. Yashin Dicente Cid, Oscar Jimenez-del-Toro, Pierre-Alexandre Poletti, Henning Müller
      Pages 372-383
    5. Fan Yang, Samadrita Roy Chowdhury, Heidi I. L. Jacobs, Keith A. Johnson, Joyita Dutta
      Pages 384-393
    6. Jiahui Li, Zhiqiang Hu, Shuang Yang
      Pages 394-404
    7. Yan Shen, Mingchen Gao
      Pages 417-428
    8. Ross Callaghan, Daniel C. Alexander, Hui Zhang, Marco Palombo
      Pages 429-440
    9. Zhihui Guo, Junjie Bai, Yi Lu, Xin Wang, Kunlin Cao, Qi Song et al.
      Pages 441-453
    10. Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion
      Pages 454-466
    11. Sheng Wang, Zheng Xu, Chaochao Yan, Junzhou Huang
      Pages 467-478
    12. Liyan Sun, Zhiwen Fan, Xinghao Ding, Yue Huang, John Paisley
      Pages 492-504

About these proceedings

Introduction

This book constitutes the proceedings of the 26th International Conference on Information Processing in Medical Imaging, IPMI 2019, held at the Hong Kong University of Science and Technology, Hong Kong, China, in June 2019.

The 69 full papers presented in this volume were carefully reviewed and selected from 229 submissions. They were organized in topical sections on deep learning and segmentation; classification and inference; reconstruction; disease modeling; shape, registration; learning motion; functional imaging; and white matter imaging. The book also includes a number of post papers. 

Keywords

artificial intelligence bayesian networks classification computer vision estimation image analysis image coding image reconstruction image segmentation imaging systems learning algorithms medical images medical imaging neural networks principal component analysis probability reconstruction semantics signal processing Support Vector Machines (SVM)

Editors and affiliations

  1. 1.Department of Computer Science and EngineeringThe Hong Kong University of Science and TechnologyHong KongChina
  2. 2.Department of RadiologyUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Department of RadiologyUniversity of PennsylvaniaPhiladelphiaUSA
  4. 4.Department of Natural Language ProcessingBaidu Inc.ShenzhenChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-20351-1
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-20350-4
  • Online ISBN 978-3-030-20351-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site