A score function as quality measure for cardiac image enhancement techniques assessment

A score function useful as a quantitative measure of the performance of the medical image enhancement techniques is reported in this paper. The measure proposed is based on merging of full–reference and blind–reference image enhancement measures. The score function is the average of the weighted sum...

Full description

Autores:
Chacón, Gerardo
Rodríguez, Johel E.
Bermúdez, Valmore
Flórez, Anderson
Del Mar, Atilio
Pardo, Aldo
Lameda, Carlos
Madriz, Delia
Bravo, Antonio J.
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
eng
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/3562
Acceso en línea:
https://hdl.handle.net/20.500.12442/3562
Palabra clave:
Image enhancement
Cardiac images
Image quality
Image enhancement assessment
Realce imágenes
Imágenes cardíacas
Calidad de imagen
Evaluación del realce de imagen
Rights
License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
id USIMONBOL2_d461656845d5382a7ee8c2d8ecf4c584
oai_identifier_str oai:bonga.unisimon.edu.co:20.500.12442/3562
network_acronym_str USIMONBOL2
network_name_str Repositorio Digital USB
repository_id_str
dc.title.eng.fl_str_mv A score function as quality measure for cardiac image enhancement techniques assessment
dc.title.alternative.spa.fl_str_mv Una función de puntuación como medida de calidad para la evaluación de técnicas de mejora de la imagen cardíaca
title A score function as quality measure for cardiac image enhancement techniques assessment
spellingShingle A score function as quality measure for cardiac image enhancement techniques assessment
Image enhancement
Cardiac images
Image quality
Image enhancement assessment
Realce imágenes
Imágenes cardíacas
Calidad de imagen
Evaluación del realce de imagen
title_short A score function as quality measure for cardiac image enhancement techniques assessment
title_full A score function as quality measure for cardiac image enhancement techniques assessment
title_fullStr A score function as quality measure for cardiac image enhancement techniques assessment
title_full_unstemmed A score function as quality measure for cardiac image enhancement techniques assessment
title_sort A score function as quality measure for cardiac image enhancement techniques assessment
dc.creator.fl_str_mv Chacón, Gerardo
Rodríguez, Johel E.
Bermúdez, Valmore
Flórez, Anderson
Del Mar, Atilio
Pardo, Aldo
Lameda, Carlos
Madriz, Delia
Bravo, Antonio J.
dc.contributor.author.none.fl_str_mv Chacón, Gerardo
Rodríguez, Johel E.
Bermúdez, Valmore
Flórez, Anderson
Del Mar, Atilio
Pardo, Aldo
Lameda, Carlos
Madriz, Delia
Bravo, Antonio J.
dc.subject.eng.fl_str_mv Image enhancement
Cardiac images
Image quality
Image enhancement assessment
topic Image enhancement
Cardiac images
Image quality
Image enhancement assessment
Realce imágenes
Imágenes cardíacas
Calidad de imagen
Evaluación del realce de imagen
dc.subject.spa.fl_str_mv Realce imágenes
Imágenes cardíacas
Calidad de imagen
Evaluación del realce de imagen
description A score function useful as a quantitative measure of the performance of the medical image enhancement techniques is reported in this paper. The measure proposed is based on merging of full–reference and blind–reference image enhancement measures. The score function is the average of the weighted sum of the image enhancement measures normalized between zero and one. The novel measure is validated considering as a hypothesis that values maximizing score function have that maximize the values of the metrics (Dice coefficient) used to evaluate certain previously reported cardiac image segmentation approach. The values of score function and Dice score reached the maximum value for the same cardiac volumes segmented.
publishDate 2019
dc.date.accessioned.none.fl_str_mv 2019-07-17T22:20:29Z
dc.date.available.none.fl_str_mv 2019-07-17T22:20:29Z
dc.date.issued.none.fl_str_mv 2019
dc.type.eng.fl_str_mv article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.identifier.issn.none.fl_str_mv 18564550
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/3562
identifier_str_mv 18564550
url https://hdl.handle.net/20.500.12442/3562
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.*.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.uri.*.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
dc.publisher.spa.fl_str_mv Sociedad Latinoamericana de Hipertensión
dc.source.spa.fl_str_mv Revista Latinoamericana de Hipertensión
Vol. 14 No. 2 (2019)
institution Universidad Simón Bolívar
dc.source.uri.eng.fl_str_mv http://caelum.ucv.ve/ojs/index.php/rev_lh/article/view/16349
bitstream.url.fl_str_mv https://bonga.unisimon.edu.co/bitstreams/0ca6758a-666e-419e-a43e-b2110fd11586/download
https://bonga.unisimon.edu.co/bitstreams/8301bb1b-0fa5-4961-bf22-c8d628a5cb6a/download
https://bonga.unisimon.edu.co/bitstreams/8266809e-98d6-4a98-ad85-b8c81f9fc93f/download
https://bonga.unisimon.edu.co/bitstreams/21951565-2675-47f7-a514-0d573525d60d/download
https://bonga.unisimon.edu.co/bitstreams/d6a1b91f-a1ae-46b7-9bb0-d4d721b9af1e/download
https://bonga.unisimon.edu.co/bitstreams/6922224c-8db1-46d5-b810-ed0d76770907/download
https://bonga.unisimon.edu.co/bitstreams/c2c69ac4-7ad0-4ad0-90ee-81f700712bdc/download
bitstream.checksum.fl_str_mv 4a2a2d9798633b32d564c4ec64ba4566
4460e5956bc1d1639be9ae6146a50347
3fdc7b41651299350522650338f5754d
fa4a4c052c7eb6f42dd86d87bcd371e3
f5903662d2282b3e9abc77c2f64fa976
249bad3d6104cc81ac5530082c22b4b7
0bdbbba869d1a4df3f2e4e879b801fff
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Digital Universidad Simón Bolívar
repository.mail.fl_str_mv repositorio.digital@unisimon.edu.co
_version_ 1814076110168653824
spelling Chacón, Gerardo09c43ece-2735-4074-9b8c-5852a95df0e4Rodríguez, Johel E.c676ecb4-6592-4c68-a85c-37fda5ef7e00Bermúdez, Valmore29f9aa18-16a4-4fd3-8ce5-ed94a0b8663aFlórez, Andersoneeff7a0b-eef1-415e-a084-10c736cdaa19Del Mar, Atilio82c097a4-4438-4c35-b8c2-f17c5324ac8bPardo, Aldo5d072c76-2eb5-4582-86ba-0510c45cb635Lameda, Carlosb1602821-ee77-4fdc-8edb-bc17489e41e1Madriz, Delia77dfe655-dfc5-4477-bda3-8b6495eb9ddaBravo, Antonio J.ebf65d70-b96f-4faf-88f7-d30c02ee68582019-07-17T22:20:29Z2019-07-17T22:20:29Z201918564550https://hdl.handle.net/20.500.12442/3562A score function useful as a quantitative measure of the performance of the medical image enhancement techniques is reported in this paper. The measure proposed is based on merging of full–reference and blind–reference image enhancement measures. The score function is the average of the weighted sum of the image enhancement measures normalized between zero and one. The novel measure is validated considering as a hypothesis that values maximizing score function have that maximize the values of the metrics (Dice coefficient) used to evaluate certain previously reported cardiac image segmentation approach. The values of score function and Dice score reached the maximum value for the same cardiac volumes segmented.En este artículo se presenta una función de puntuación útil como medida cuantitativa del rendimiento de técnicas de mejora de imágenes médicas. La métrica propuesta se basa en la fusión de medidas de mejora de imagen de referencia completa y referencia ciega. La función de puntuación es el promedio de la suma ponderada de las medidas de mejora de imagen normalizadas entre cero y uno. La nueva medida se valida considerando la hipótesis de que los valores que maximizan la función de puntuación tienen como máximo los valores de las métricas (coeficiente de Dice) utilizados para evaluar cierto enfoque de segmentación de imágenes cardíacas reportado previamente. Los valores de la función de puntuación y el coeficiente de Dice alcanzaron el valor máximo para los mismos volúmenes cardíacos segmentados.engSociedad Latinoamericana de HipertensiónAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2Revista Latinoamericana de HipertensiónVol. 14 No. 2 (2019)http://caelum.ucv.ve/ojs/index.php/rev_lh/article/view/16349Image enhancementCardiac imagesImage qualityImage enhancement assessmentRealce imágenesImágenes cardíacasCalidad de imagenEvaluación del realce de imagenA score function as quality measure for cardiac image enhancement techniques assessmentUna función de puntuación como medida de calidad para la evaluación de técnicas de mejora de la imagen cardíacaarticlehttp://purl.org/coar/resource_type/c_6501Rangayyan, R. Biomedical Image Analysis. CRC Press, USA, 2005.Kruger, R. X-ray digital cineangiocardiography, in: Collins, S., Skorton, D. (Eds.), Cardiac imaging and image processing. McGraw–Hill, USA, 1986Faletra, F., Pandian, N., Ho, S. Anatomy of the Heart by Multislice Computed Tomography. Wiley, UK, 2008Li, H., Hu, W., Xu, Z. Automatic no–reference image quality assessment. SpringerPlus. 2016; 5(1):1097.Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E. Image quality assessment: From error visibility to structural similarity. IEEE Trans. Image Processing. 2004; 13(4):600–612.Pitas, I., Venetsanopoulos, A. Order statistics in digital image processing. Proc. IEEE. 1992; 80(12):1893–1921.Rosenfeld, A., Kak, A., 1982. Digital Picture Processing. Volume 1. Academic Press.Gabarda, S., Cristóbal, G. Blind image quality assessment through anisotropy. J. Opt. Soc. Am. A. 2007; 24(12):B42–B51.Girod, B., 1993. What’s wrong with mean-squared error?, in: Watson, A. (Ed.), Digital Images and Human Vision. MIT Press, USA, pp. 207–220.Wang, Z., Bovik, A. Mean squared error: Love it or leave it? a new look at signal fidelity measures. IEEE Signal Processing Mag. 2009; 26(1):98–117.Wang, Z., Li, Q. Information content weighting for perceptual image quality assessment. IEEE Trans. Image Processing. 2011; 20(5):1185– 1198.Wang, S., Ma, K., Yeganeh, H., Wang, Z., Lin, W. A patch–structure representation method for quality assessment of contrast changed images. IEEE Signal Processing Lett. 2015; 22(12):2387–2390.Loizou, C., Theofanous, C., Pantziaris, M., Kasparis, T. Despeckle filtering software toolbox for ultrasound imaging of the common carotid artery. Comput. Methods Prog. Biomed. 2014; 114(1):109–124.Agaian, S., Panetta, K., Grigoryan, A. A new measure of image enhancement, in: IASTED Int. Conf. Sign. Proc. & Commun., Spain. pp. 19–22, 2000.Hecht, S. The visual discrimination of intensity and the Weber–Fechner Law. J. Gen. Physiol. 1924; 7(2):235–267.Jacko, J. Human–Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications. CRC Press, USA, 2012.Michelson, A. Studies in Optics. The University of Chicago Press, USA, 1927.Agaian, S., Panetta, K., Grigoryan, A. Transform-based image enhancement algorithms with performance measure. IEEE Trans. Image Processing. 2001; 10(3):367–382.DelMarco, S., Agaian, S. The design of wavelets for image enhancement and target detection, in: Proc. SPIE Mobile Multimedia/Image Process., Security, Appl., Orlando, USA. pp. 735103–1–735103–12, 2009.Panetta, K., Zhou, Y., Agaian, S., Jia, H. Nonlinear unsharp masking for mammogram enhancement. IEEE Trans. Inform. Technol. Biomed. 2011; 15(6):918–928.Nercessian, S., Agaian, S., Panetta, K. Multi–scale image enhancement using a second derivative –likemeasure of contrast. Proc. SPIE 8295, 82950Q–82950Q–9, 2012.Aubury, M., Luk, W. Binomial filters. J VLSI Signal Process Syst Signal Image Video Technol. 1996; 12(1):35–50.Arce, G. A general weighted median filter structure admitting negative weights. IEEE Trans. Image Processing. 1998; 46(12):3195–3205.Schroeder, W., Martin, K., Lorensen, B. The Visualization Toolkit–An Object-Oriented Approach To 3D Graphics. Fourth ed., Kitware, Inc, 2006.Vera, M. [Cardiac structures segmentation in multislice computerized images]. Ph.D. thesis. Universidad de Los Andes. Mérida, Venezuela. In Spanish, 2014.Barrett, J., Keat, N. Artifacts in CT: Recognition and avoidance1. Radio- Graph. 2004; 24(6):1679–1691.Primak, A., McCollough, C., Bruesewitz, M., Zhang, J., Fletcher, J. Relationship between noise, dose, and pitch in cardiac multi–detector row CT. RadioGraph. 2006; 26(6):1785–1794.ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf368736https://bonga.unisimon.edu.co/bitstreams/0ca6758a-666e-419e-a43e-b2110fd11586/download4a2a2d9798633b32d564c4ec64ba4566MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://bonga.unisimon.edu.co/bitstreams/8301bb1b-0fa5-4961-bf22-c8d628a5cb6a/download4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8368https://bonga.unisimon.edu.co/bitstreams/8266809e-98d6-4a98-ad85-b8c81f9fc93f/download3fdc7b41651299350522650338f5754dMD53TEXTAscorefunctionasqualitymeasure.pdf.txtAscorefunctionasqualitymeasure.pdf.txtExtracted texttext/plain32411https://bonga.unisimon.edu.co/bitstreams/21951565-2675-47f7-a514-0d573525d60d/downloadfa4a4c052c7eb6f42dd86d87bcd371e3MD54PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain32959https://bonga.unisimon.edu.co/bitstreams/d6a1b91f-a1ae-46b7-9bb0-d4d721b9af1e/downloadf5903662d2282b3e9abc77c2f64fa976MD56THUMBNAILAscorefunctionasqualitymeasure.pdf.jpgAscorefunctionasqualitymeasure.pdf.jpgGenerated Thumbnailimage/jpeg1963https://bonga.unisimon.edu.co/bitstreams/6922224c-8db1-46d5-b810-ed0d76770907/download249bad3d6104cc81ac5530082c22b4b7MD55PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg6602https://bonga.unisimon.edu.co/bitstreams/c2c69ac4-7ad0-4ad0-90ee-81f700712bdc/download0bdbbba869d1a4df3f2e4e879b801fffMD5720.500.12442/3562oai:bonga.unisimon.edu.co:20.500.12442/35622024-08-14 21:52:33.592http://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 Internacionalopen.accesshttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.coPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj48aW1nIGFsdD0iTGljZW5jaWEgQ3JlYXRpdmUgQ29tbW9ucyIgc3R5bGU9ImJvcmRlci13aWR0aDowIiBzcmM9Imh0dHBzOi8vaS5jcmVhdGl2ZWNvbW1vbnMub3JnL2wvYnktbmMvNC4wLzg4eDMxLnBuZyIgLz48L2E+PGJyLz5Fc3RhIG9icmEgZXN0w6EgYmFqbyB1bmEgPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj5MaWNlbmNpYSBDcmVhdGl2ZSBDb21tb25zIEF0cmlidWNpw7NuLU5vQ29tZXJjaWFsIDQuMCBJbnRlcm5hY2lvbmFsPC9hPi4=

Publicaciones similares