Pre-processing of Retinal Images for Removal of Outliers
- PDF / 2,054,555 Bytes
- 26 Pages / 439.37 x 666.142 pts Page_size
- 82 Downloads / 221 Views
(0123456789().,-volV)(0123456789().,-volV)
Pre-processing of Retinal Images for Removal of Outliers Niharika Thakur1 • Mamta Juneja1 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Early diagnosis of diseases related with retina such as glaucoma is of utmost importance in current scenario as it is the second most prevailing cause of irreversible blindness over the world and is expected to increase further in near future. It is commonly diagnosed using retinal images which are acquired by digital fundus cameras. But the acquired images may be prone to certain outliers that create hindrance in diagnosis of glaucoma by tempering the accuracy. These outliers include retinal vessels, low contrast of images and uneven illumination that deteriorates the performance of disc and cup segmentation which are the key indicators to diagnose glaucoma. Thus, pre-processing of retinal images to remove outliers plays a significant role in diagnosis. This paper presents an approach for pre-processing the retinal fundus image followed by its comparison with state of the art. Based on the experimental analysis the performance of the proposed approach is found to be better than the state of the art based on the analysis using metrics such as peak signal to ratio, mean square error and structural similarity index. Further, the proposed approach has been compared with state of the art using metrics such as Jaccard index and dice similarity on the basis of segmentation outcomes on different pre-processing approaches. Keywords Retinal images Pre-processing Glaucoma Outliers
1 Introduction Retinal fundus imaging is an essential imaging modality used for analysis of interior structure of eyes. It is primarily used to diagnose the physiological or pathological alterations within the retina in a non-invasive and less time-consuming manner. Retinal images are acquired using fundus camera that is based on the principle of monocular indirect ophthalmoscope, that means observations and illuminations follow dissimilar paths. The intrinsic flexibility of this imaging allows applications in various clinical tasks for diagnosis of retinal diseases. Early diagnosis of diseases related with retina such as glaucoma is of utmost importance in current scenario as it is the second most prevailing reason of & Mamta Juneja [email protected] Niharika Thakur [email protected] 1
Computer Science and Engineering, University Institute and Engineering and Technology, Panjab University, Chandigarh, India
123
N. Thakur, M. Juneja
blindness over the world and is expected to increase further in near future [1]. Research studies on glaucoma shows that the retinal image used for diagnosis purpose are prone to certain outliers such as nonuniformity, vessels and low contrast which create hindrance in further analysis for diagnosis [1]. Retinal images are particular type of eye images acquired using the fundus cameras for diagnosis of diverse types of retinal abnormalities. These images are captured under the supervisio
Data Loading...
