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Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction

Medical imaging help medical doctors provide faster and more efficient diagnoses to their patients. Medical image quality directly influences diagnosis. However, when medical images are acquired, they often present degradations such as poor detail or low contrast. This work presents an algorithm tha...

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Main Author: Mello Román, Julio César (author)
Other Authors: Escobar Torres, Ricardo Daniel (author), Martínez Martínez, Fabiola Beatriz (author), Vázquez Noguera, José Luis (author), Legal Ayala, Horacio Andrés (author), Pinto Roa, Diego Pedro (author)
Format: article
Language:English
Published: 2020
Subjects:
Low contrast
Medical imaging
Multiscale top-hat transform by reconstruction
Natural brightness
Online Access:https://doi.org/10.1016/j.entcs.2020.02.013
http://hdl.handle.net/20.500.14066/4589
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_version_ 1870612066913484800
author Mello Román, Julio César
author2 Escobar Torres, Ricardo Daniel
Martínez Martínez, Fabiola Beatriz
Vázquez Noguera, José Luis
Legal Ayala, Horacio Andrés
Pinto Roa, Diego Pedro
author2_role author
author
author
author
author
author_browse Escobar Torres, Ricardo Daniel
Legal Ayala, Horacio Andrés
Martínez Martínez, Fabiola Beatriz
Mello Román, Julio César
Pinto Roa, Diego Pedro
Vázquez Noguera, José Luis
author_facet Mello Román, Julio César
Escobar Torres, Ricardo Daniel
Martínez Martínez, Fabiola Beatriz
Vázquez Noguera, José Luis
Legal Ayala, Horacio Andrés
Pinto Roa, Diego Pedro
author_role author
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dc.contributor.other.es.fl_str_mv Universidad Nacional de Asunción. Facultad Politécnica
dc.creator.none.fl_str_mv Mello Román, Julio César
Escobar Torres, Ricardo Daniel
Martínez Martínez, Fabiola Beatriz
Vázquez Noguera, José Luis
Legal Ayala, Horacio Andrés
Pinto Roa, Diego Pedro
dc.date.accessioned.none.fl_str_mv 2025-06-11T15:34:15Z
dc.date.available.none.fl_str_mv 2025-06-11T15:34:15Z
dc.date.issued.none.fl_str_mv 2020-07-31
dc.identifier.citation.en.fl_str_mv Mello Román, J. C., Escobar, R., Martínez, F., Vázquez Noguera, J. L., Legal-Ayala, H., & Pinto-Roa, D. P. (2020). Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction. Electronic Notes in Theoretical Computer Science, 349, 69-80. https://doi.org/10.1016/j.entcs.2020.02.013
dc.identifier.doi.es.fl_str_mv 10.1016/j.entcs.2020.02.013
dc.identifier.issn.es.fl_str_mv 1571-0661
dc.identifier.other.es.fl_str_mv https://doi.org/10.1016/j.entcs.2020.02.013
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.14066/4589
dc.language.iso.es.fl_str_mv eng
dc.publisher.es.fl_str_mv Elsevier
dc.relation.projectCONACYT.es.fl_str_mv POSG17-53
dc.rights.*.fl_str_mv Atribución 4.0 Internacional
dc.rights.accessRights.es.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by/4.0/
dc.subject.other.es.fl_str_mv Low contrast
Medical imaging
Multiscale top-hat transform by reconstruction
Natural brightness
dc.title.es.fl_str_mv Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
dc.type.es.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description Medical imaging help medical doctors provide faster and more efficient diagnoses to their patients. Medical image quality directly influences diagnosis. However, when medical images are acquired, they often present degradations such as poor detail or low contrast. This work presents an algorithm that improves contrast and detail, preserving the natural brightness of medical images. The proposed method is based on multiscale top-hat transform by reconstruction. It extracts multiple features from the image that are then used to enhance the medical image. To quantify the performance of the proposed method, 100 medical images from a public database were used. Experiments show that the proposal improves contrast, introducing less distortion and preserving the average brightness of medical images.
eu_rights_str_mv openAccess
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id CONACYT_3be2116cc1a2baa4907b33a2daa64be3
identifier_str_mv Mello Román, J. C., Escobar, R., Martínez, F., Vázquez Noguera, J. L., Legal-Ayala, H., & Pinto-Roa, D. P. (2020). Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction. Electronic Notes in Theoretical Computer Science, 349, 69-80. https://doi.org/10.1016/j.entcs.2020.02.013
1571-0661
10.1016/j.entcs.2020.02.013
language eng
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network_name_str Repositorio Institucional CONACYT
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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
rights_invalid_str_mv Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
spelling 126060047542e12-0bd8-4cc5-9491-fd72c000f76a600dab306da-07e8-4033-9bf9-b1b6d641673a60011446006466009026000000-0003-2479-9876Universidad Nacional de Asunción. Facultad Politécnica2025-06-11T15:34:15Z2025-06-11T15:34:15Z2020-07-31Mello Román, J. C., Escobar, R., Martínez, F., Vázquez Noguera, J. L., Legal-Ayala, H., & Pinto-Roa, D. P. (2020). Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction. Electronic Notes in Theoretical Computer Science, 349, 69-80. https://doi.org/10.1016/j.entcs.2020.02.0131571-0661https://doi.org/10.1016/j.entcs.2020.02.013http://hdl.handle.net/20.500.14066/458910.1016/j.entcs.2020.02.013Medical imaging help medical doctors provide faster and more efficient diagnoses to their patients. Medical image quality directly influences diagnosis. However, when medical images are acquired, they often present degradations such as poor detail or low contrast. This work presents an algorithm that improves contrast and detail, preserving the natural brightness of medical images. The proposed method is based on multiscale top-hat transform by reconstruction. It extracts multiple features from the image that are then used to enhance the medical image. To quantify the performance of the proposed method, 100 medical images from a public database were used. Experiments show that the proposal improves contrast, introducing less distortion and preserving the average brightness of medical images.Consejo Nacional de Ciencia y TecnologíaPrograma Paraguayo para el Desarrollo de la Ciencia y Tecnología. Proyectos de creación y fortalecimiento de maestrías y doctorados de excelenciaengElsevierAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccess© 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Low contrastMedical imagingMultiscale top-hat transform by reconstructionNatural brightnessMedical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstructioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionElectronic Notes in Theoretical Computer Science6980POSG17-53349Mello Román, Julio CésarEscobar Torres, Ricardo DanielMartínez Martínez, Fabiola BeatrizVázquez Noguera, José LuisLegal Ayala, Horacio AndrésPinto Roa, Diego PedroORIGINALMedical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction.pdfMedical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction.pdfArtículo científicoapplication/pdf1066356http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4589/1/Medical%20image%20enhancement%20with%20brightness%20and%20detail%20preserving%20using%20multiscale%20top-hat%20transform%20by%20reconstruction.pdff2c37eb745609e94cc89166f7d467d14MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; 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spellingShingle Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
Mello Román, Julio César
Low contrast
Medical imaging
Multiscale top-hat transform by reconstruction
Natural brightness
status_str publishedVersion
title Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
title_full Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
title_fullStr Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
title_full_unstemmed Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
title_short Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
title_sort Medical image enhancement with brightness and detail preserving using multiscale top-hat transform by reconstruction
topic Low contrast
Medical imaging
Multiscale top-hat transform by reconstruction
Natural brightness
url https://doi.org/10.1016/j.entcs.2020.02.013
http://hdl.handle.net/20.500.14066/4589

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