Retinal image enhancement via a multiscale morphological approach with OCCO filter.
Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the vis...
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| Altres autors: | , , , |
| Format: | article |
| Idioma: | anglès |
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2020
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| Accés en línia: | http://hdl.handle.net/20.500.14066/3797 |
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| _version_ | 1870612072881979392 |
|---|---|
| author | Mello Román, Julio César |
| author2 | Vázquez Noguera, José Luis García Torres, Miguel Castillo, Veronica Elisa Castro Matto, Ingrid |
| author2_role | author author author author |
| author_browse | Castillo, Veronica Elisa Castro Matto, Ingrid García Torres, Miguel Mello Román, Julio César Vázquez Noguera, José Luis |
| author_facet | Mello Román, Julio César Vázquez Noguera, José Luis García Torres, Miguel Castillo, Veronica Elisa Castro Matto, Ingrid |
| author_role | author |
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| bitstream.checksumAlgorithm.fl_str_mv | MD5 MD5 MD5 |
| bitstream.url.fl_str_mv | http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/1/PINV18-846art1.pdf http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/2/license.txt http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/3/PINV18-846art1.pdf.txt |
| dc.contributor.other.es.fl_str_mv | Universidad Nacional de Concepción - Facultad de Medicina (PY) Universidad Pablo de Olavide (ES) |
| dc.creator.none.fl_str_mv | Mello Román, Julio César Vázquez Noguera, José Luis García Torres, Miguel Castillo, Veronica Elisa Castro Matto, Ingrid |
| dc.date.accessioned.none.fl_str_mv | 2022-04-29T23:13:33Z |
| dc.date.available.none.fl_str_mv | 2022-04-29T23:13:33Z |
| dc.date.issued.none.fl_str_mv | 2020 |
| dc.identifier.doi.es.fl_str_mv | 10.1007/978-3-030-68285-9_18 |
| dc.identifier.uri.none.fl_str_mv | http://hdl.handle.net/20.500.14066/3797 |
| dc.language.iso.es.fl_str_mv | eng |
| dc.relation.projectCONACYT.es.fl_str_mv | PINV18-846 |
| dc.rights.accessRights.es.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.classification.es.fl_str_mv | 1303 I+D en relación con las Ciencias médicas |
| dc.subject.other.es.fl_str_mv | RETINAL IMAGES CONTRAST ENHANCEMENT MATHEMATICAL MOR PHOLOGY TOP-HAT TRANSFORM |
| dc.title.es.fl_str_mv | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| dc.type.es.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded reti nal images. In this work, a novel algorithm based on multi-scale mathe matical morphology is presented. First, the original image is blurred us ing the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art al gorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | CONACYT_e36e7f1d9c81285ad80628d47ab615fb |
| identifier_str_mv | 10.1007/978-3-030-68285-9_18 |
| language | eng |
| network_acronym_str | CONACYT |
| network_name_str | Repositorio Institucional CONACYT |
| oai_identifier_str | oai:repositorio.conacyt.gov.py:20.500.14066/3797 |
| publishDate | 2020 |
| publishDateSort | 2020 |
| repository.mail.fl_str_mv | repositorio.institucional@conacyt.gov.py |
| repository.name.fl_str_mv | Repositorio Institucional CONACYT |
| repository_id_str | |
| spelling | 11bddad9-f33b-43c9-8169-2cb6feaa29de6001144600386292aa-adcb-4977-a6aa-08b85eb571e060084782119-1768-4c44-838e-440839f303d8600e22e0e61-768d-40bd-8ba2-641719f6ac1a600Universidad Nacional de Concepción - Facultad de Medicina (PY)Universidad Pablo de Olavide (ES)2022-04-29T23:13:33Z2022-04-29T23:13:33Z2020http://hdl.handle.net/20.500.14066/379710.1007/978-3-030-68285-9_18Retinal images are widely used for diagnosis and eye disease detection. However, due to the acquisition process, retinal images often have problems such as low contrast, blurry details or artifacts. These problems may severely affect the diagnosis. Therefore, it is very impor tant to enhance the visual quality of such images. Contrast enhancement is a pre-processing applied to images to improve their visual quality. This technique betters the identification of retinal structures in degraded reti nal images. In this work, a novel algorithm based on multi-scale mathe matical morphology is presented. First, the original image is blurred us ing the Open-Close Close-Open (OCCO) filter to reduce any artifacts in the image. Next, multiple bright and dark features are extracted from the filtered image by the Top-Hat transform. Finally, the maximum bright values are added to the original image and the maximum dark values are subtracted from the original image, previously adjusted by a weight. The algorithm was tested on 397 retinal images from the public STARE database. The proposed algorithm was compared with state of the art al gorithms and results show that the proposal is more efficient in improving contrast, maintaining similarity with the original image and introducing less distortion than the other algorithms. According to ophthalmologists, the algorithm, by improving retinal images, provides greater clarity in the blood vessels of the retina and would facilitate the identification of pathologies.Consejo Nacional de Ciencia y TecnologíaPROCIENCIAeng1303 I+D en relación con las Ciencias médicasRETINAL IMAGESCONTRAST ENHANCEMENTMATHEMATICAL MOR PHOLOGYTOP-HAT TRANSFORMRetinal image enhancement via a multiscale morphological approach with OCCO filter.info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion186Information Technology and SystemsPINV18-846info:eu-repo/semantics/openAccess177Mello Román, Julio CésarVázquez Noguera, José LuisGarcía Torres, MiguelCastillo, Veronica ElisaCastro Matto, IngridORIGINALPINV18-846art1.pdfPINV18-846art1.pdfPINV18-846art1application/pdf1417664http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/1/PINV18-846art1.pdfb504faa21a83742a693862d4c8fa242fMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81698http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/2/license.txt858b22fda432bd774e469302988c1974MD52TEXTPINV18-846art1.pdf.txtPINV18-846art1.pdf.txtExtracted texttext/plain20475http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3797/3/PINV18-846art1.pdf.txt3c1fc99d1854f7a6d743680049fa6438MD5320.500.14066/3797oai:repositorio.conacyt.gov.py:20.500.14066/37972026-02-12 19:30:32.318Repositorio Institucional CONACYTrepositorio.institucional@conacyt.gov.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 |
| spellingShingle | Retinal image enhancement via a multiscale morphological approach with OCCO filter. Mello Román, Julio César 1303 I+D en relación con las Ciencias médicas RETINAL IMAGES CONTRAST ENHANCEMENT MATHEMATICAL MOR PHOLOGY TOP-HAT TRANSFORM |
| status_str | publishedVersion |
| title | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| title_full | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| title_fullStr | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| title_full_unstemmed | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| title_short | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| title_sort | Retinal image enhancement via a multiscale morphological approach with OCCO filter. |
| topic | 1303 I+D en relación con las Ciencias médicas RETINAL IMAGES CONTRAST ENHANCEMENT MATHEMATICAL MOR PHOLOGY TOP-HAT TRANSFORM |
| url | http://hdl.handle.net/20.500.14066/3797 |