DeepAI AI Chat
Log In Sign Up

RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology

by   Chen gong, et al.

Retinal template matching and registration is an important challenge in teleophthalmology with low-cost imaging devices. However, the images from such devices generally have a small field of view (FOV) and image quality degradations, making matching difficult. In this work, we develop an efficient and accurate retinal matching technique that combines dimension reduction and mutual information (MI), called RetinaMatch. The dimension reduction initializes the MI optimization as a coarse localization process, which narrows the optimization domain and avoids local optima. The effectiveness of RetinaMatch is demonstrated on the open fundus image database STARE with simulated reduced FOV and anticipated degradations, and on retinal images acquired by adapter-based optics attached to a smartphone. RetinaMatch achieves a success rate over 94% on human retinal images with the matched target registration errors below 2 pixels on average, excluding the observer variability. It outperforms the standard template matching solutions. In the application of measuring vessel diameter repeatedly, single pixel errors are expected. In addition, our method can be used in the process of image mosaicking with area-based registration, providing a robust approach when the feature based methods fail. To the best of our knowledge, this is the first template matching algorithm for retina images with small template images from unconstrained retinal areas. In the context of the emerging mixed reality market, we envision automated retinal image matching and registration methods as transformative for advanced teleophthalmology and long-term retinal monitoring.


page 1

page 3

page 5

page 7

page 9

page 10


GLAMpoints: Greedily Learned Accurate Match points

We introduce a novel CNN-based feature point detector - GLAMpoints - lea...

Optimal Transport-based Graph Matching for 3D retinal OCT image registration

Registration of longitudinal optical coherence tomography (OCT) images a...

Sparse And Low Rank Decomposition Based Batch Image Alignment for Speckle Reduction of retinal OCT Images

Optical Coherence Tomography (OCT) is an emerging technique in the field...

A Neural Template Matching Method to Detect Knee Joint Areas

In this paper, new methods are considered to detect knee joint areas in ...

Robust and efficient computation of retinal fractal dimension through deep approximation

A retinal trait, or phenotype, summarises a specific aspect of a retinal...

How could we ignore the lens and pupils of eyeballs: Metamaterial optics for retinal projection

Retinal projection is required for xR applications that can deliver imme...