Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy

Maziyar M. Khansari, Jiong Zhang, Yuchuan Qiao, Jin Kyu Gahm, Mona Sharifi Sarabi, Amir H. Kashani, Yonggang Shi

Research output: Contribution to journalArticlepeer-review

Abstract

Diabetic retinopathy (DR) is a significant microvascular complication of diabetes mellitus and a leading cause of vision impairment in working age adults. Optical coherence tomography (OCT) is a routinely used clinical tool to observe retinal structural and thickness alterations in DR. Pathological changes that alter the normal anatomy of the retina, such as intraretinal edema, pose great challenges for conventional layer-based analysis of OCT images. We present an alternative approach for the automated analysis of OCT volumes in DR research based on nonlinear registration. In this paper, we first obtain an anatomically consistent volume of interest (VOI) in different OCT images via carefully designed masking and affine registration. After that, efficient B-spline transformations are computed using stochastic gradient descent optimization. Using the OCT volumes of normal controls, for which layer-based segmentation works well, we demonstrate the accuracy of our registration-based analysis in aligning layer boundaries. By nonlinearly registering the OCT volumes of DR subjects to an atlas constructed from normal controls and measuring the Jacobian determinant of the deformation, we can simultaneously visualize tissue contraction and expansion due to DR pathology. Tensor-based morphometry (TBM) can also be performed for quantitative analysis of local structural changes. In our experimental results, we apply our method to a dataset of 105 subjects and demonstrate that volumetric OCT registration and TBM analysis can successfully detect local retinal structural alterations due to DR.

Original languageEnglish (US)
Article number8744275
Pages (from-to)236-245
Number of pages10
JournalIEEE transactions on medical imaging
Volume39
Issue number1
DOIs
StatePublished - Jan 2020
Externally publishedYes

Keywords

  • 3D image registration
  • diabetic retinopathy
  • Optical coherence tomography
  • tensor-based morphometry

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy'. Together they form a unique fingerprint.

Cite this