Accurate detection of diabetic retinopathy (DR) mainly depends on identification of retinal landmarks such as optic disc and fovea. Present methods suffer from challenges like less accuracy and high computational complexity. To address this issue, this paper presents a novel approach for fast and accurate localization of optic disc (OD) and fovea using one-dimensional scanned intensity profile analysis. The proposed method utilizes both time and frequency domain information effectively for localization of OD. The final OD center is located using signal peak-valley detection in time domain and discontinuity detection in frequency domain analysis. However, with the help of detected OD location, the fovea center is located using signal valley analysis. Experiments were conducted on MESSIDOR dataset, where OD was successfully located in 1197 out of 1200 images (99.75%) and fovea in 1196 out of 1200 images (99.66%) with an average computation time of 0.52s. The large scale evaluation has been carried out extensively on nine publicly available databases. The proposed method is highly efficient in terms of quickly and accurately localizing OD and fovea structure together compared with the other state-of-the-art methods.
Identification of retinal landmarks is an important step in the extraction of anomalies in retinal fundus images. In the current study, we propose a technique to identify and localize the position of macula and hence the fovea avascular zone, in colour fundus images. The proposed method, based on varying blur scales in images, is independent of the location of other anatomical landmarks present in the fundus images. Experimental results have been provided using the open database MESSIDOR by validating our segmented regions using the dice coefficient, with ground truth segmentation provided by a human expert. Apart from testing the images on the entire MESSIDOR database, the proposed technique was also validated using 50 normal and 50 diabetic retinopathy chosen digital fundus images from the same database. A maximum overlap accuracy of 89.6%-93.8% and locational accuracy of 94.7%-98.9% was obtained for identification and localization of the fovea.
A 24 year-old Malay lady presented with high grade fever, myalgia, generalized rashes, severe headache and was positive for dengue serology test. Her lowest platelet count was 45 × 10(9) cells/L. She complained of sudden onset of painlessness, profound loss of vision bilaterally 7 days after the onset of fever. On examination, her right eye best corrected vision was 6/30 and left eye was 6/120. Her anterior segment examination was unremarkable. Funduscopy revealed there were multiple retinal haemorrhages found at posterior pole of both fundi and elevation at fovea area with subretinal fluid. Systemic examination revealed normal findings except for residual petechial rashes. She was managed conservatively. Her vision improved tremendously after 2 months. The retinal hemorrhages and foveal elevation showed sign of resolving. Ocular manifestations following dengue fever is rare. However, bilateral visual loss can occur if both fovea are involved.
Monitoring FAZ area enlargement enables physicians to monitor progression of the DR. At present, it is difficult to discern the FAZ area and to measure its enlargement in an objective manner using digital fundus images. A semi-automated approach for determination of FAZ using color images has been developed. Here, a binary map of retinal blood vessels is computer generated from the digital fundus image to determine vessel ends and pathologies surrounding FAZ for area analysis. The proposed method is found to achieve accuracies from 66.67% to 98.69% compared to accuracies of 18.13-95.07% obtained by manual segmentation of FAZ regions from digital fundus images.
To describe the usage of 100% perfluoropropane and subsequent laser retinopexy for the repair of posterior pole retinal detachment in a previously vitrectomised patient with diabetic tractional detachment.