Recurrent Self Fusion: Iterative Denoising for Consistent Retinal OCT Segmentation-Reference-Cited by-同舟云学术

Recurrent Self Fusion: Iterative Denoising for Consistent Retinal OCT Segmentation

Published:2023 Issue: Volume: Page:42-51
ISSN:0302-9743
Container-title:Ophthalmic Medical Image Analysis
language:
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Author:

Wei Shuwen^ORCID,Liu Yihao^ORCID,Bian Zhangxing^ORCID,Wang Yuli,Zuo Lianrui^ORCID,Calabresi Peter A.^ORCID,Saidha Shiv,Prince Jerry L.^ORCID,Carass Aaron^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-44013-7_5

Reference21 articles.

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2. Balakrishnan, G., Zhao, A., Sabuncu, M.R., Guttag, J., Dalca, A.V.: Voxelmorph: a learning framework for deformable medical image registration. IEEE Trans. Med. Imag. 38(8), 1788–1800 (2019)

3. Bhargava, P., et al.: Applying an open-source segmentation algorithm to different OCT devices in multiple sclerosis patients and healthy controls: implications for clinical trials. Multiple Sclerosis Int. 2015 (2015)

4. Chiu, S.J., Allingham, M.J., Mettu, P.S., Cousins, S.W., Izatt, J.A., Farsiu, S.: Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema. Biomed. Opt. Express 6(4), 1172–1194 (2015)

5. He, Y., et al.: Structured layer surface segmentation for retina OCT using fully convolutional regression networks. Med. Image Anal. 68, 101856 (2021)

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