Deep convolutional network based on rank learning for OCT retinal images quality assessment

Jia Yang Wang, Lei Zhang, Min Zhang, Jun Feng, Yi Lv

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The visual quality measurement of optical coherence tomography (OCT) images is very important for the diagnosis of diseases in the later stage. This paper presented a novel OCT image quality assessment method. The concept of pairwise learning in learning to rank (LTR) is introduced to extract image features sensitive to OCT image quality levels. First, a simple multi-input network (Ranking-based OCT image features extraction network) is constructed by using the residual structure. Second, the ROFE Network is trained by pairwise images. Third, the trained ROFE Network is used to extract the ranking sensitive features of OCT images. Finally, support vector regression (SVR) model is used to get the objective quality scores of OCT images. In order to verify the effectiveness of the proposed method, 608 OCT images with subjective perceptual quality are collected, and a number of experiments are carried out. The experimental results show the proposed method has strong correlations with subjective quality evaluations.

Original languageEnglish
Title of host publicationMedical Imaging 2019
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
EditorsBarjor Gimi, Andrzej Krol
PublisherSPIE
ISBN (Electronic)9781510625532
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes
EventMedical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, United States
Duration: 19 Feb 201921 Feb 2019

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10953
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/TerritoryUnited States
CitySan Diego
Period19/02/1921/02/19

Keywords

  • Deep Convolutional Network
  • Image quality assessment (IQA)
  • Learning to rank
  • Optical coherence tomography (OCT)

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

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