Harnessing group-sparsity regularization for resolution enhancement of lung 4D-CT

Arnav Bhavsar, Guorong Wu, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A critical concern with lung 4D-CT is the low superior-inferior resolution, due to the consideration of radiation dose. We propose a resolution enhancement approach that reconstructs missing intermediate slices by exploiting the idea that information lost in one respiratory phase can be found in others, according to the complimentary nature of inter-phase information. Our approach is based on a patch-based framework that explores the role of group-sparsity involving groups of similar neighbouring patches. We discuss the regularizing role of group-sparsity, which helps in reducing the effect of noise and enables better enhancement of anatomical structures. Our results positively demonstrate the potential of group-sparsity for 4D-CT resolution enhancement.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings
Pages139-146
Number of pages8
EditionPART 3
DOIs
Publication statusPublished - 2013
Event16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: 2013 Sep 222013 Sep 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume8151 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
CountryJapan
CityNagoya
Period13/9/2213/9/26

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Bhavsar, A., Wu, G., & Shen, D. (2013). Harnessing group-sparsity regularization for resolution enhancement of lung 4D-CT. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings (PART 3 ed., pp. 139-146). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8151 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-40760-4_18