Login / Signup

Usefulness of Denoising Process to Depict Myopic Choroidal Neovascularisation Using a Single Optical Coherence Tomography Angiography Image.

Yuka SawaiManabu MiyataAkihito UjiSotaro OotoHiroshi TamuraNaoko Ueda-ArakawaYuki MuraokaMasahiro MiyakeAyako TakahashiYu KawashimaShin KadomotoYasuyuki OritaniKentaro KawaiKenji YamashiroAkitaka Tsujikawa
Published in: Scientific reports (2020)
Quality of single optical coherence tomography angiography (OCTA) images of myopic choroidal neovascularisation (mCNV) is poorer than in averaged images, although obtaining averaged images takes much time. This study evaluated the clinical usefulness of novel denoising process for depicting mCNV. This study included 20 eyes of 20 patients with mCNV. Ten en face images taken in a 3 × 3 mm macular cube were obtained from outer-retina-to-choriocapillaris layer. Three image types were prepared for analysis; single images before and after the denoising process accomplished deep learning (single and denoising groups, respectively) and up to 10 images were averaged (averaging group). Pairwise comparisons showed vessel density, vessel length density, and fractal dimension (FD) were higher; whereas, vessel density index (VDI) was lower in single group than in denoising and averaging groups. Detectable CNV indices, contrast-to-nose ratio, and CNV diagnostic scores were higher in denoising and averaging groups than in single group. No significant differences were detected in VDI, FD, or CNV diagnostic scores between denoising and averaging groups. The denoising process can utilise single OCTA images to provide results comparable to averaged OCTA images, which is clinically useful for shortening examination times with quality similar to averaging.
Keyphrases
  • convolutional neural network
  • deep learning
  • optical coherence tomography
  • artificial intelligence
  • diabetic retinopathy
  • image quality
  • computed tomography
  • magnetic resonance imaging
  • optic nerve