Diagnosis of Retinitis Pigmentosa from Retinal Images
Retinitis pigmentosa is a genetic disorder that results in nyctalopia and its progression leads to complete loss of vision. The analysis and the study of retinal images are necessary, so as to help ophthalmologist in early detection of the retinitis pigmentosa. In this paper fundus images and Optica...
| Huvudupphovsmän: | , , |
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| Materialtyp: | Artikel |
| Språk: | English |
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Polish Academy of Sciences
2019-09-01
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| Serie: | International Journal of Electronics and Telecommunications |
| Ämnen: | |
| Länkar: | https://journals.pan.pl/Content/113312/PDF/70.pdf |
| _version_ | 1828325960867381248 |
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| author | Giritharan Ravichandran Poonguzhali Elangovan Malaya Kumar Nath |
| author_facet | Giritharan Ravichandran Poonguzhali Elangovan Malaya Kumar Nath |
| author_sort | Giritharan Ravichandran |
| collection | DOAJ |
| description | Retinitis pigmentosa is a genetic disorder that results in nyctalopia and its progression leads to complete loss of vision. The analysis and the study of retinal images are necessary, so as to help ophthalmologist in early detection of the retinitis pigmentosa. In this paper fundus images and Optical Coherence Tomography images are comprehensively analyzed, so as to obtain the various morphological features that characterize the retinitis pigmentosa. Pigment deposits, important trait of RP is investigated. Degree of darkness and entropy are the features used for analysis of PD. The darkness and entropy of the PD is compared with the different regions of the fundus image which is used to detect the pigments in the retinal image. Also the performance of the proposed algorithm is evaluated by using various performance metrics. The performance metrics are calculated for all 120 images of RIPS dataset. The performance metrics such as sensitivity, sensibility, specificity, accuracy, F-score, equal error rate, conformity coefficient, Jaccard’s coefficient, dice coefficient, universal quality index were calculated as 0.72, 0.96, 0.97, 0.62, 0.12, 0.09, 0.59, 0.45 and 0.62, respectively. |
| first_indexed | 2024-04-13T19:31:02Z |
| format | Article |
| id | doaj.art-5fda9c2048a647ddb7e00a11f73c943f |
| institution | Directory Open Access Journal |
| issn | 2081-8491 2300-1933 |
| language | English |
| last_indexed | 2024-04-13T19:31:02Z |
| publishDate | 2019-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj.art-5fda9c2048a647ddb7e00a11f73c943f2022-12-22T02:33:10ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332019-09-01vol. 65No 3https://doi.org/10.24425/ijet.2019.129808Diagnosis of Retinitis Pigmentosa from Retinal ImagesGiritharan RavichandranPoonguzhali ElangovanMalaya Kumar NathRetinitis pigmentosa is a genetic disorder that results in nyctalopia and its progression leads to complete loss of vision. The analysis and the study of retinal images are necessary, so as to help ophthalmologist in early detection of the retinitis pigmentosa. In this paper fundus images and Optical Coherence Tomography images are comprehensively analyzed, so as to obtain the various morphological features that characterize the retinitis pigmentosa. Pigment deposits, important trait of RP is investigated. Degree of darkness and entropy are the features used for analysis of PD. The darkness and entropy of the PD is compared with the different regions of the fundus image which is used to detect the pigments in the retinal image. Also the performance of the proposed algorithm is evaluated by using various performance metrics. The performance metrics are calculated for all 120 images of RIPS dataset. The performance metrics such as sensitivity, sensibility, specificity, accuracy, F-score, equal error rate, conformity coefficient, Jaccard’s coefficient, dice coefficient, universal quality index were calculated as 0.72, 0.96, 0.97, 0.62, 0.12, 0.09, 0.59, 0.45 and 0.62, respectively.https://journals.pan.pl/Content/113312/PDF/70.pdfretinitis pigmentosapigment depositsretinal fundus imageblood vessel extractionwatershed segmentation |
| spellingShingle | Giritharan Ravichandran Poonguzhali Elangovan Malaya Kumar Nath Diagnosis of Retinitis Pigmentosa from Retinal Images International Journal of Electronics and Telecommunications retinitis pigmentosa pigment deposits retinal fundus image blood vessel extraction watershed segmentation |
| title | Diagnosis of Retinitis Pigmentosa from Retinal Images |
| title_full | Diagnosis of Retinitis Pigmentosa from Retinal Images |
| title_fullStr | Diagnosis of Retinitis Pigmentosa from Retinal Images |
| title_full_unstemmed | Diagnosis of Retinitis Pigmentosa from Retinal Images |
| title_short | Diagnosis of Retinitis Pigmentosa from Retinal Images |
| title_sort | diagnosis of retinitis pigmentosa from retinal images |
| topic | retinitis pigmentosa pigment deposits retinal fundus image blood vessel extraction watershed segmentation |
| url | https://journals.pan.pl/Content/113312/PDF/70.pdf |
| work_keys_str_mv | AT giritharanravichandran diagnosisofretinitispigmentosafromretinalimages AT poonguzhalielangovan diagnosisofretinitispigmentosafromretinalimages AT malayakumarnath diagnosisofretinitispigmentosafromretinalimages |