© 2019

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

About these proceedings


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. 


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