- Tytuł:
- Denoising methods for improving automatic segmentation in OCT images of human eye
- Autorzy:
-
Stankiewicz, A.
Marciniak, T.
Dąbrowski, A.
Stopa, M.
Rakowicz, P.
Marciniak, E. - Powiązania:
- https://bibliotekanauki.pl/articles/201133.pdf
- Data publikacji:
- 2017
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
optical coherence tomography (OCT)
image denoising
image segmentation
anisotropic diffusion
wavelet thresholding
koherentna tomografia optyczna
OCT
segmentacja obrazu
dyfuzja anizotropowa - Opis:
- This paper presents analysis of selected noise reduction methods used in optical coherence tomography (OCT) retina images (the socalled B-scans). The tested algorithms include median and averaging filtering, anisotropic diffusion, soft wavelet thresholding, and multiframe wavelet thresholding. Precision of the denoising process was evaluated based on the results of automated retina layers segmentation, since this stage (vital for ophthalmic diagnosis) is strongly dependent on the image quality. Experiments were conducted with a set of 3D low quality scans obtained from 10 healthy patients and 10 patients with vitreoretinal pathologies. Influence of each method on the automatic image segmentation for both groups of patients is thoroughly described. Manual annotations of investigated retina layers provided by ophthalmology experts served as reference data for evaluation of the segmentation algorithm.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2017, 65, 1; 71-78
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł