Automated localisation of optic disc in retinal colour fundus image for assisting in the diagnosis of glaucoma

Abstract

Optic disc (OD), especially its diameter together with optic cup diameter can be used as a feature to diagnose glaucoma. This study contains two main steps for optic disc localisation, i.e. OD centre point detection and OD diameter determination. Centre point of OD is obtained by finding brightness pixel value based on average filtering. After that, OD diameter is measured from the detected optic disc boundary. The proposed scheme is validated on 30 healthy and glaucoma retinal fundus images from HRF database. The results are compared to the ground truth images. The proposed scheme obtains evaluation result (E) for healthy and glaucoma images is 0.23 and 0.21, respectively. Evaluation result (E) shows the ratio between the average distance of OD centre point obtained by proposed method and that of the ground truth divided by average difference between OD diameter by proposed method and that of the ground truth. The lesser the value of E the better the performance of the method in detecting OD centre point and determining the OD diameter. Therefore, these results indicate successful implementation of automated OD localisation by detecting OD centre point and determining OD diameter in healthy and glaucoma images. Moreover, this scheme has a potential to be implemented in the development of a computerised glaucoma diagnosis system.

Optic cup segmentation using adaptive threshold and morphological image processing

“…After that, the optic disc localization process is conducted to gain information about the optic cup. The localization of the optic disc is performed by choosing the highest pixel intensity [12] as the center point of the optic disc region. This region is defined as a region of interest (RoI) used in the next process.…”

“…Moreover, not any different with TP and TN, every miss is equal to score '1' for every FP and FN that happened in the matching process. After matching all the pixels of the ground truth and segmentation result, the accuracy, specificity and sensitivity is measured by using (11), (12) and (13).…”

Detection of Optic Disc Centre Point in Retinal Image

“…The retinal fundus image whether from Messidor or HRF database consists of three components, namely the Red, Green and Blue (RGB) Channels. The RGB (Red, Green, and Blue) colour space is one of the most used colour spaces, particularly for 8 bit digital images as expressed in (2-1) [8][20] [21]. Red channel is the brightest image, the green channel has the best contrast and the blue channel image has the worse brightness and contrast [6].…”