Statistical atlas-based descriptor for an early detection of optic disc abnormalities.
نویسندگان
چکیده
Optic disc (OD) appearance in fundus images is one of the clinical indicators considered in the assessment of retinal diseases such as glaucoma. The cup-to-disc ratio (CDR) is the most common clinical measurement used to characterize glaucoma. However, the CDR only evaluates the relative sizes of the cup and the OD via their diameters. We propose to construct an atlas-based shape descriptor (ASD) to statistically characterize the geometric deformations of the OD shape and of the blood vessels' configuration inside the OD region. A local representation of the OD region is proposed to construct a well-defined statistical atlas using nonlinear registration and statistical analysis of deformation fields. The shape descriptor is defined as being composed of several statistical measures from the atlas. Analysis of the average model and its principal modes of deformation are performed on a healthy population. The components of the ASD show a significant difference between pathological and healthy ODs. We show that the ASD is able to characterize healthy and glaucomatous OD regions. The deviation map extracted from the atlas can be used to assist clinicians in an early detection of deformation abnormalities in the OD region.
منابع مشابه
Morphological Exudate Detection in Retinal Images using PCA-based Optic Disc Removal
Diabetic retinopathy lesion detection such as exudate in fundus image of retina can lead to early diagnosis of the disease. Retinal image includes dark areas such as main blood vessels and retinal tissue and also bright areas such as optic disk, optical fibers and lesions e.g. exudate. In this paper, a multistage algorithm for the detection of exudate in foreground is proposed. The algorithm se...
متن کاملAutomatic Optic Disc Center and Boundary Detection in Color Fundus Images
Accurately detection of retinal landmarks, like optic disc, is an important step in the computer aided diagnosis frameworks. This paper presents an efficient method for automatic detection of the optic disc’s center and estimating its boundary. The center and initial diameter of optic disc are estimated by employing an ANN classifier. The ANN classifier employs visual features of vessels and th...
متن کاملSegmentation and Detection of Optic Disc Using Kmeans Clustering
Diabetic retinopathy and glaucoma are one of the major cause of blindness. Early stage segmentation and detection of optic disc may be of great help to ophthalmologist for treatment of patient before any serious complications. In this paper new methodology is proposed for the detection of the optical disk from the retinal images. Input image is first preprocessed using spatial average filtering...
متن کاملEarly Detection of Glaucoma Based on Local Binary Pattern and Unsupervised Clustering Approaches Using Fundus Images
Glaucoma is the second leading progressive ocular disorder after cataract caused by degenerative optic nerve head (ONH) structure. To minimize the risk of visual loss and impairment, early detection of glaucoma is needed. Among the various image structural cues for glaucoma detection, most of the clinician considered Cup-to-Disc (CDR) ratio as major factor. Hence, an robust and automated early ...
متن کاملEvaluation of Retinal Optic Disc Segmentation in Patients with Glaucoma and Comparison with Other Methods of Medical Image Processing
Introduction: Glaucoma is the most common cause of blindness in some countries. In the meantime, the field of retinal image processing has been proposed in order to provide automatic systems for disease diagnosis. Among the methods of medical image processing, image segmentation is a process of identification and change in the display of an image. The objective of this study was to use t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Journal of medical imaging
دوره 5 1 شماره
صفحات -
تاریخ انتشار 2018