Details
| Original language | English |
|---|---|
| Title of host publication | Ophthalmic Technologies XXXV |
| Editors | Daniel X. Hammer, Derek Nankivil, Yuankai K. Tao |
| Publisher | SPIE |
| ISBN (electronic) | 9781510683488 |
| Publication status | Published - 19 Mar 2025 |
| Event | SPIE Photonics West BiOS 2025 - San Francisco, United States Duration: 25 Jan 2025 → 31 Jan 2025 |
Publication series
| Name | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
|---|---|
| Volume | 13300 |
| ISSN (Print) | 1605-7422 |
Abstract
This work presents a software-based approach for robust feature tracking of funduscopy images. In our specific application, it is utilized in a scannerless linear optical coherence tomography system, where both natural and directed eye movements are used to scan the retina. The approach developed includes a fast, contrast-enhancing video preprocessing step. Additional filtering highlights edges and details, enhancing the visibility of blood vessels and the optic disc. Reflections are removed, both those arising from the funduscopy setup itself and non-stationary reflections caused by the cornea or an intraocular lens. A state-of-the-art feature detector and descriptor is used to identify and characterize distinctive image regions. Subsequent feature matching and filtering include additional criteria to enhance robustness against outliers and false detections. From these final matches, homographies are calculated, allowing the derivation of relative movements and absolute positions. The results demonstrate real-time processing with high detection rates and minimal misdetections. This performance is maintained even in the presence of poor contrast and non-stationary reflections in the original video stream. While the tracking is optimized for our application, it is also applicable to other domains, such as optimizing the alignment of retinal images, generating wide-field panorama images from individual frames, or characterizing eye movements.
Keywords
- Computer Vision, Funduscopy, Image Enhancement, Motion Tracking, Ophthalmic Imaging, Retina, Video Processing
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Materials Science(all)
- Biomaterials
- Medicine(all)
- Radiology Nuclear Medicine and imaging
Cite this
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- Harvard
- Apa
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- BibTeX
- RIS
Ophthalmic Technologies XXXV. ed. / Daniel X. Hammer; Derek Nankivil; Yuankai K. Tao. SPIE, 2025. 133000L (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 13300).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Robust real-time retinal tracking for ophthalmic applications
AU - Mendroch, Damian
AU - Harings, David
AU - Bauer, Niklas
AU - Altmeyer, Stefan
AU - Oberheide, Uwe
AU - Heisterkamp, Alexander
N1 - Publisher Copyright: © 2025 SPIE.
PY - 2025/3/19
Y1 - 2025/3/19
N2 - This work presents a software-based approach for robust feature tracking of funduscopy images. In our specific application, it is utilized in a scannerless linear optical coherence tomography system, where both natural and directed eye movements are used to scan the retina. The approach developed includes a fast, contrast-enhancing video preprocessing step. Additional filtering highlights edges and details, enhancing the visibility of blood vessels and the optic disc. Reflections are removed, both those arising from the funduscopy setup itself and non-stationary reflections caused by the cornea or an intraocular lens. A state-of-the-art feature detector and descriptor is used to identify and characterize distinctive image regions. Subsequent feature matching and filtering include additional criteria to enhance robustness against outliers and false detections. From these final matches, homographies are calculated, allowing the derivation of relative movements and absolute positions. The results demonstrate real-time processing with high detection rates and minimal misdetections. This performance is maintained even in the presence of poor contrast and non-stationary reflections in the original video stream. While the tracking is optimized for our application, it is also applicable to other domains, such as optimizing the alignment of retinal images, generating wide-field panorama images from individual frames, or characterizing eye movements.
AB - This work presents a software-based approach for robust feature tracking of funduscopy images. In our specific application, it is utilized in a scannerless linear optical coherence tomography system, where both natural and directed eye movements are used to scan the retina. The approach developed includes a fast, contrast-enhancing video preprocessing step. Additional filtering highlights edges and details, enhancing the visibility of blood vessels and the optic disc. Reflections are removed, both those arising from the funduscopy setup itself and non-stationary reflections caused by the cornea or an intraocular lens. A state-of-the-art feature detector and descriptor is used to identify and characterize distinctive image regions. Subsequent feature matching and filtering include additional criteria to enhance robustness against outliers and false detections. From these final matches, homographies are calculated, allowing the derivation of relative movements and absolute positions. The results demonstrate real-time processing with high detection rates and minimal misdetections. This performance is maintained even in the presence of poor contrast and non-stationary reflections in the original video stream. While the tracking is optimized for our application, it is also applicable to other domains, such as optimizing the alignment of retinal images, generating wide-field panorama images from individual frames, or characterizing eye movements.
KW - Computer Vision
KW - Funduscopy
KW - Image Enhancement
KW - Motion Tracking
KW - Ophthalmic Imaging
KW - Retina
KW - Video Processing
UR - http://www.scopus.com/inward/record.url?scp=105004219757&partnerID=8YFLogxK
U2 - 10.1117/12.3047657
DO - 10.1117/12.3047657
M3 - Conference contribution
AN - SCOPUS:105004219757
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Ophthalmic Technologies XXXV
A2 - Hammer, Daniel X.
A2 - Nankivil, Derek
A2 - Tao, Yuankai K.
PB - SPIE
T2 - SPIE Photonics West BiOS 2025
Y2 - 25 January 2025 through 31 January 2025
ER -