Retinal slit lamp video mosaicking

De Zanet, Sandro; Rudolph, Tobias; Richa, Rogerio; Tappeiner, Christoph; Sznitman, Raphael (2016). Retinal slit lamp video mosaicking. International Journal of Computer Assisted Radiology and Surgery, 11(6), pp. 1035-1041. Springer 10.1007/s11548-016-1377-4

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Purpose

To this day, the slit lamp remains the first tool used by an ophthalmologist to examine patient eyes. Imaging of the retina poses, however, a variety of problems, namely a shallow depth of focus, reflections from the optical system, a small field of view and non-uniform illumination. For ophthalmologists, the use of slit lamp images for documentation and analysis purposes, however, remains extremely challenging due to large image artifacts. For this reason, we propose an automatic retinal slit lamp video mosaicking, which enlarges the field of view and reduces amount of noise and reflections, thus enhancing image quality.
Methods

Our method is composed of three parts: (i) viable content segmentation, (ii) global registration and (iii) image blending. Frame content is segmented using gradient boosting with custom pixel-wise features. Speeded-up robust features are used for finding pair-wise translations between frames with robust random sample consensus estimation and graph-based simultaneous localization and mapping for global bundle adjustment. Foreground-aware blending based on feathering merges video frames into comprehensive mosaics.
Results

Foreground is segmented successfully with an area under the curve of the receiver operating characteristic curve of 0.9557. Mosaicking results and state-of-the-art methods were compared and rated by ophthalmologists showing a strong preference for a large field of view provided by our method.
Conclusions

The proposed method for global registration of retinal slit lamp images of the retina into comprehensive mosaics improves over state-of-the-art methods and is preferred qualitatively.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Ophthalmology
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Medical Imaging Laboratory

UniBE Contributor:

De Zanet, Sandro, Rudolph, Tobias, Tappeiner, Christoph, Sznitman, Raphael

Subjects:

600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

ISSN:

1861-6410

Publisher:

Springer

Language:

English

Submitter:

Raphael Sznitman

Date Deposited:

11 May 2016 15:47

Last Modified:

05 Dec 2022 14:54

Publisher DOI:

10.1007/s11548-016-1377-4

PubMed ID:

26995602

BORIS DOI:

10.7892/boris.80224

URI:

https://boris.unibe.ch/id/eprint/80224

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