Registration of retinal sequences from new video-ophthalmoscopic camera. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Kolar, Radim; Tornow, Ralf.; Odstrcilik, Jan; Liberdova, Ivana
• Is Part Of: Biomedical engineering online. Volume 15:Issue 1(2016)
• Page Start: 1
• Page End: 17
• Publication Date: 2016-12
• Subjects: Retinal imaging -- Video-ophthalmoscopy -- Image registration -- Tracking; Biomedical engineering -- Periodicals; 610.2805
• DOI: 10.1186/s12938-016-0191-0
• Languages: English
• ISSNs: 1475-925X

Abstract

Abstract Background Analysis of fast temporal changes on retinas has become an important part of diagnostic video-ophthalmology. It enables investigation of the hemodynamic processes in retinal tissue, e.g. blood-vessel diameter changes as a result of blood-pressure variation, spontaneous venous pulsation influenced by intracranial-intraocular pressure difference, blood-volume changes as a result of changes in light reflection from retinal tissue, and blood flow using laser speckle contrast imaging. For such applications, image registration of the recorded sequence must be performed. Methods Here we use a new non-mydriatic video-ophthalmoscope for simple and fast acquisition of low SNR retinal sequences. We introduce a novel, two-step approach for fast image registration. The phase correlation in the first stage removes large eye movements. Lucas-Kanade tracking in the second stage removes small eye movements. We propose robust adaptive selection of the tracking points, which is the most important part of tracking-based approaches. We also describe a method for quantitative evaluation of the registration results, based on vascular tree intensity profiles. Results The achieved registration error evaluated on 23 sequences (5840 frames) is 0.78 ± 0.67 pixels inside the optic disc and 1.39 ± 0.63 pixels outside the optic disc. We compared the results with the commonly used approaches based on Lucas-Kanade tracking and scale-invariant feature transform, which achieved worse results. Conclusion The proposed method can efficiently correct particular frames of retinal sequences for shift and rotation. The registration results for each frame (shift inX andY direction and eye rotation) can also be used for eye-movement evaluation during single-spot fixation tasks.