DOTE: Dual convolutional filter learning for super-resolution and cross-modality synthesis in MRI

Yawen Huang, Ling Shao, Alejandro F Frangi

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Cross-modal image synthesis is a topical problem in medical image computing. Existing methods for image synthesis are either tailored to a specific application, require large scale training sets, or are based on partitioning images into overlapping patches. In this paper, we propose a novel Dual cOnvolutional filTer lEarning (DOTE) approach to overcome the drawbacks of these approaches. We construct a closed loop joint filter learning strategy that generates informative feedback for model self-optimization. Our method can leverage data more efficiently thus reducing the size of the required training set. We extensively evaluate DOTE in two challenging tasks: image super-resolution and cross-modality synthesis. The experimental results demonstrate superior performance of our method over other state-of-the-art methods.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
EditorsLena Maier-Hein, Alfred Franz, Pierre Jannin, Simon Duchesne, Maxime Descoteaux, D. Louis Collins
PublisherSpringer-Verlag Italia
Pages89-98
Number of pages10
ISBN (Print)9783319661780
DOIs
Publication statusPublished - 2017
Event20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 11 Sept 201713 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10435 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
Country/TerritoryCanada
CityQuebec City
Period11/09/1713/09/17

Keywords

  • 3D
  • Convolutional sparse coding
  • Dual learning
  • Image synthesis
  • MRI
  • Multi-modal

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