Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction
| Title: | Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction |
|---|---|
| Authors: | Li, Shijie, Alexopoulos, Palaiologos, Vellappally, Anse, Zambrano, Ronald, Gadi, Wollstein, Gerig, Guido |
| Publication Year: | 2023 |
| Collection: | Computer Science |
| Subject Terms: | Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition |
| More Details: | Strong speckle noise is inherent to optical coherence tomography (OCT) imaging and represents a significant obstacle for accurate quantitative analysis of retinal structures which is key for advances in clinical diagnosis and monitoring of disease. Learning-based self-supervised methods for structure-preserving noise reduction have demonstrated superior performance over traditional methods but face unique challenges in OCT imaging. The high correlation of voxels generated by coherent A-scan beams undermines the efficacy of self-supervised learning methods as it violates the assumption of independent pixel noise. We conduct experiments demonstrating limitations of existing models due to this independence assumption. We then introduce a new end-to-end self-supervised learning framework specifically tailored for OCT image denoising, integrating slice-by-slice training and registration modules into one network. An extensive ablation study is conducted for the proposed approach. Comparison to previously published self-supervised denoising models demonstrates improved performance of the proposed framework, potentially serving as a preprocessing step towards superior segmentation performance and quantitative analysis. Comment: 5 pages, 4 figures, 1 table, submitted to International Symposium on Biomedical Imaging 2024 |
| Document Type: | Working Paper |
| Access URL: | http://arxiv.org/abs/2311.15167 |
| Accession Number: | edsarx.2311.15167 |
| Database: | arXiv |
| FullText | Text: Availability: 0 CustomLinks: – Url: http://arxiv.org/abs/2311.15167 Name: EDS - Arxiv Category: fullText Text: View this record from Arxiv MouseOverText: View this record from Arxiv – Url: https://resolver.ebsco.com/c/xy5jbn/result?sid=EBSCO:edsarx&genre=article&issn=&ISBN=&volume=&issue=&date=20231125&spage=&pages=&title=Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction&atitle=Self-supervised%20OCT%20Image%20Denoising%20with%20Slice-to-Slice%20Registration%20and%20Reconstruction&aulast=Li%2C%20Shijie&id=DOI: Name: Full Text Finder (for New FTF UI) (s8985755) Category: fullText Text: Find It @ SCU Libraries MouseOverText: Find It @ SCU Libraries |
|---|---|
| Header | DbId: edsarx DbLabel: arXiv An: edsarx.2311.15167 RelevancyScore: 1065 AccessLevel: 3 PubType: Report PubTypeId: report PreciseRelevancyScore: 1065.28576660156 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Shijie%22">Li, Shijie</searchLink><br /><searchLink fieldCode="AR" term="%22Alexopoulos%2C+Palaiologos%22">Alexopoulos, Palaiologos</searchLink><br /><searchLink fieldCode="AR" term="%22Vellappally%2C+Anse%22">Vellappally, Anse</searchLink><br /><searchLink fieldCode="AR" term="%22Zambrano%2C+Ronald%22">Zambrano, Ronald</searchLink><br /><searchLink fieldCode="AR" term="%22Gadi%2C+Wollstein%22">Gadi, Wollstein</searchLink><br /><searchLink fieldCode="AR" term="%22Gerig%2C+Guido%22">Gerig, Guido</searchLink> – Name: DatePubCY Label: Publication Year Group: Date Data: 2023 – Name: Subset Label: Collection Group: HoldingsInfo Data: Computer Science – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Electrical+Engineering+and+Systems+Science+-+Image+and+Video+Processing%22">Electrical Engineering and Systems Science - Image and Video Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+-+Computer+Vision+and+Pattern+Recognition%22">Computer Science - Computer Vision and Pattern Recognition</searchLink> – Name: Abstract Label: Description Group: Ab Data: Strong speckle noise is inherent to optical coherence tomography (OCT) imaging and represents a significant obstacle for accurate quantitative analysis of retinal structures which is key for advances in clinical diagnosis and monitoring of disease. Learning-based self-supervised methods for structure-preserving noise reduction have demonstrated superior performance over traditional methods but face unique challenges in OCT imaging. The high correlation of voxels generated by coherent A-scan beams undermines the efficacy of self-supervised learning methods as it violates the assumption of independent pixel noise. We conduct experiments demonstrating limitations of existing models due to this independence assumption. We then introduce a new end-to-end self-supervised learning framework specifically tailored for OCT image denoising, integrating slice-by-slice training and registration modules into one network. An extensive ablation study is conducted for the proposed approach. Comparison to previously published self-supervised denoising models demonstrates improved performance of the proposed framework, potentially serving as a preprocessing step towards superior segmentation performance and quantitative analysis.<br />Comment: 5 pages, 4 figures, 1 table, submitted to International Symposium on Biomedical Imaging 2024 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Working Paper – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="http://arxiv.org/abs/2311.15167" linkWindow="_blank">http://arxiv.org/abs/2311.15167</link> – Name: AN Label: Accession Number Group: ID Data: edsarx.2311.15167 |
| PLink | https://login.libproxy.scu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&scope=site&db=edsarx&AN=edsarx.2311.15167 |
| RecordInfo | BibRecord: BibEntity: Subjects: – SubjectFull: Electrical Engineering and Systems Science - Image and Video Processing Type: general – SubjectFull: Computer Science - Computer Vision and Pattern Recognition Type: general Titles: – TitleFull: Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Shijie – PersonEntity: Name: NameFull: Alexopoulos, Palaiologos – PersonEntity: Name: NameFull: Vellappally, Anse – PersonEntity: Name: NameFull: Zambrano, Ronald – PersonEntity: Name: NameFull: Gadi, Wollstein – PersonEntity: Name: NameFull: Gerig, Guido IsPartOfRelationships: – BibEntity: Dates: – D: 25 M: 11 Type: published Y: 2023 |
| ResultId | 1 |