Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) imaging technique, a CAD system in retinal OCT is essential to assist ophthalmologist in the early detection of ocular diseases and treatment monitoring. This paper presents a novel CAD system based on a multi-scale convolutional mixture of expert (MCME) ensemble model to identify normal retina, and two common types of macular pathologies, namely, dry age-related macular degeneration, and diabetic macular edema. The proposed MCME modular model is a data-driven neural structure, which employs a new cost function for discriminative and fast learning of image features by applying convolutional neural networks on multiple-scale sub-images. MCME maximizes the likelihood function of the training data set and ground truth by considering a mixture model, which tries also to model the joint interaction between individual experts by using a correlated multivariate component for each expert module instead of only modeling the marginal distributions by independent Gaussian components. Two different macular OCT data sets from Heidelberg devices were considered for the evaluation of the method, i.e., a local data set of OCT images of 148 subjects and a public data set of 45 OCT acquisitions. For comparison purpose, we performed a wide range of classification measures to compare the results with the best configurations of the MCME method. With the MCME model of four scale-dependent experts, the precision rate of 98.86%, and the area under the receiver operating characteristic curve (AUC) of 0.9985 were obtained on average.
Posttraumatic endophthalmitis is more likely among patients with open-globe injury that are needle related and among those who have intraocular foreign bodies, traumatic lens rupture, smaller wounds, or wounds exclusively in the cornea. Lower ocular trauma scores in this group of patients with penetrating trauma indicated a greater risk of poor visual prognosis. Therefore, it is suggested that necessary measures and immediate treatment be undertaken in high-risk patients.
The most prevalent trauma etiology is a projectile metallic foreign body in adults and a knife injury in children. Compared with other previous epidemiologic studies, we had younger patients, lower enucleations, and sympathetic ophthalmia.
The introduction of enhanced depth imaging optical coherence tomography (EDI-OCT) has provided the advantage of in vivo cross-sectional imaging of the choroid, similar to the retina, with standard commercially available spectral domain (SD) OCT machines. A texture-based algorithm is introduced in this paper for fully automatic segmentation of choroidal images obtained from an EDI system of Heidelberg 3D OCT Spectralis. Dynamic programming is utilized to determine the location of the retinal pigment epithelium (RPE). Bruch's membrane (BM) (the blood-retina barrier which separates the RPE cells of the retina from the choroid) can be segmented by searching for the pixels with the biggest gradient value below the RPE. Furthermore, a novel method is proposed to segment the choroid-sclera interface (CSI), which employs the wavelet based features to construct a Gaussian mixture model (GMM). The model is then used in a graph cut for segmentation of the choroidal boundary. The proposed algorithm is tested on 100 EDI OCTs and is compared with manual segmentation. The results showed an unsigned error of 2.48 ± 0.32 pixels for BM extraction and 9.79 ± 3.29 pixels for choroid detection. It implies significant improvement of the proposed method over other approaches like k-means and graph cut methods.
<H4>BACKGROUND AND OBJECTIVE</H4> <P>To evaluate the efficacy and safety of the pars plana Ahmed glaucoma valve (New World Medical, Inc., Rancho Cucamonga, CA) implant combined with pars plana vitrectomy and panretinal photocoagulation for the management of neovascular glaucoma in patients with vitreous hemorrhage.</P> <H4>PATIENTS AND METHODS</H4> <P>The records of 18 eyes of 17 consecutive patients with neovascular glaucoma who had undergone pars plana vitrectomy and pars plana Ahmed valve implant were evaluated. The patients were observed for a mean time of 14.2 months (range, 6 to 28 months).</P> <H4>RESULTS</H4> <P>Mean preoperative intraocular pressure with oral and two or three topical antiglaucoma medications was 53.3 ± 10 mm Hg, and mean postoperative intraocular pressure without oral antiglaucoma medications was 16.3 ± 7.1 mm Hg (<I>P</I> < .0001) at the final visit. Overall success rate was 72.2%, defined as an intraocular pressure of 5 to 21 mm Hg with or without antiglaucoma medication. A postoperative hypertensive phase occurred in 7 patients (38.8%), of which all but one responded to medical therapy. Visual acuity was stabilized or improved in 77.7% of the eyes. There was one case of each of the following adverse events: mild vitreous cavity hemorrhage, hypotony, choroidal effusion, epiretinal membrane, corneal edema, and corneal ulcer. Two cases developed phthisis bulbi and lost light perception.</P> <H4>CONCLUSIONS</H4> <P>Pars plana vitrectomy and Ahmed valve implantation seems to be a viable surgical modality in the management of neovascular glaucoma and coexisting posterior segment pathology with a relatively low rate of serious permanent postoperative complications.</P> <P>[<CITE>Ophthalmic Surg Lasers Imaging</CITE> 2007;38:292- 300.]</P> <H4>AUTHORS</H4> <P>From the Eye Research Center (HF, FH, S-FM, AK, MR-E), Farabi Eye Hospital, Tehran University of Medical Sciences, Tehran, Iran; and the Department of Ophthalmology (GAP), University of Arizona College of Medicine, Tucson, Arizona.</P> <P>Accepted for publication January 20, 2007.</P> <P>Address correspondence to Gholam A. Peyman, MD, University of Arizona College of Medicine, 655 N. Alvernon Way, Suite 108, Tucson, AZ 85711.</P>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.