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Approximate nearest neighbour field based optic disk detection.

S Avinash Ramakanth¹, R Venkatesh Babu¹

¹Video Analytics Lab, Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560 012, India.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society

|December 3, 2013

Summary

This summary is machine-generated.

This study introduces Approximate Nearest Neighbour Field (ANNF) maps for optic disk detection in retinal images. The novel method achieves 99% accuracy, advancing medical image analysis.

Keywords:

Approximate Nearest Neighbour Field FeatureMatch Fundus or retinal image processing Optic disk detection

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Area of Science:

Medical Image Analysis
Computer Vision
Retinal Imaging

Background:

Approximate Nearest Neighbour Field (ANNF) maps are widely used in computer vision and graphics for tasks like image completion and denoising.
Optic disk detection is crucial in retinal image analysis for segmenting the optic disk and other structures.

Purpose of the Study:

To extend the application of ANNF maps to medical image analysis, specifically for optic disk detection in retinal images.
To develop an efficient and accurate method for identifying the optic disk in fundus images.

Main Methods:

The proposed approach utilizes FeatureMatch, an ANNF algorithm, to establish correspondences between a reference optic disk image and query retinal images.
A likelihood map is generated from the distribution of matching image patches to detect the optic disk.

Main Results:

The method was evaluated on 1540 images across five public databases (DIARETDB0, DIARETDB1, DRIVE, STARE, MESSIDOR).
Achieved an average detection accuracy of 99% with an average computation time of 0.2 seconds per image.

Conclusions:

The ANNF-based approach demonstrates high accuracy and efficiency for optic disk detection in retinal images.
This method offers a valuable tool for automated analysis in ophthalmology and medical imaging research.