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Volumetrically tracking retinal and choroidal structural changes in central serous chorioretinopathy.

Bingjie WangRichard BrownJay ChhablaniShaohua Pi
Published in: bioRxiv : the preprint server for biology (2023)
Central serous chorioretinopathy (CSCR) leads to accumulation of subretinal fluid and retinal thickness change, which can be readily detected in clinics using optical coherence tomography (OCT). However, current quantification methods usually require sophisticated processing such as retinal layer segmentations, and volumetric visualization of structural changes is generally challenging, which can hinder fast and accurate assessment of disease progression and/or treatment efficacy. In this study, we developed an algorithm that can register the OCT scans acquired from different visits without requiring prior layer segmentation and calculated the three-dimensional (3-D) structural change maps for patients with CSCR. Our results demonstrate that this tool can be useful in monitoring the progression of CSCR and revealing the resolution of pathologies following treatment automatically with minimal pre-processing.
Keyphrases
  • optical coherence tomography
  • diabetic retinopathy
  • optic nerve
  • high grade
  • deep learning
  • primary care
  • computed tomography
  • machine learning
  • magnetic resonance imaging
  • high resolution
  • replacement therapy