Fast fully-automated multimodal image co-registration (optical coherence tomography, colour fundus photography, red-free, fluorescein angiography)

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Abstract

Purpose

To automatically co-register optical coherence tomography (OCT), colour fundus photography (CFP), red-free (RF) and fluorescein angiography (FA).

Methods

The burden of manually assisted co-registration and the number of images taken per day prevent its widespread use. An algorithm able to co-register images in between the major modalities in due time is herewith proposed. Typically, OCT fundus references translate into a poorly detailed vascular network, thus rendering difficult its co-registration to other imaging modalities. A recently developed method (by our group) to compute the vascular network from OCT to the level of detail of CFP was used. A set of vessel features is computed and an iterative process estimates the transformation required to co-register these locations. At each step the number of inliers is determined and the process repeats. Images of 20 eyes from 13 patients that underwent high-definition OCT, CFP and FA, were co-registered. These images were manually segmented by a grader. Two additional sets were co-registered and evaluated by an expert: 102 OCT/CFP image pairs from 51 subjects, and 40 FA/RF image pairs from 20 patients.

Results

A skeleton overlap metric was defined and computed based on the vessels skeleton (0–no overlap, 1-full overlap) for the first set. An average overlap of 0.93±0.03 (N=60) is reported. From the expert evaluation, 91% of images were successfully co-registered. For the registration of a given pair, the algorithm takes 1.68±0.38 seconds on an Intel Core i7-2600k, 3.4 GHz computer.

Conclusion

The achieved level of co-registration, render this process an asset to the clinical daily practice and research.

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