Renal lithiasis detection in uro-computed tomography using a non-parametric technique

Renal lithiasis is the pathology that causes nephritic colic, which is one of the most frequent reasons for consultation in emergency medical services. According to the size, location, hardness and number of stones present in the urinary system, usually in the human kidney, it is established to whic...

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Autores:
Rodríguez-Ibáñez, R
Vera, M I
Vera, M
Gelvez-Almeida, E
Huérfano, Y
Valbuena, O
Salazar-Torres, 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:20.500.12442/5070
Acceso en línea:
https://hdl.handle.net/20.500.12442/5070
Palabra clave:
Renal lithiasis
Urinary system
Computed tomography images
Kidney stones
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License
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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dc.title.eng.fl_str_mv Renal lithiasis detection in uro-computed tomography using a non-parametric technique
title Renal lithiasis detection in uro-computed tomography using a non-parametric technique
spellingShingle Renal lithiasis detection in uro-computed tomography using a non-parametric technique
Renal lithiasis
Urinary system
Computed tomography images
Kidney stones
title_short Renal lithiasis detection in uro-computed tomography using a non-parametric technique
title_full Renal lithiasis detection in uro-computed tomography using a non-parametric technique
title_fullStr Renal lithiasis detection in uro-computed tomography using a non-parametric technique
title_full_unstemmed Renal lithiasis detection in uro-computed tomography using a non-parametric technique
title_sort Renal lithiasis detection in uro-computed tomography using a non-parametric technique
dc.creator.fl_str_mv Rodríguez-Ibáñez, R
Vera, M I
Vera, M
Gelvez-Almeida, E
Huérfano, Y
Valbuena, O
Salazar-Torres, J
dc.contributor.author.none.fl_str_mv Rodríguez-Ibáñez, R
Vera, M I
Vera, M
Gelvez-Almeida, E
Huérfano, Y
Valbuena, O
Salazar-Torres, J
dc.subject.eng.fl_str_mv Renal lithiasis
Urinary system
Computed tomography images
Kidney stones
topic Renal lithiasis
Urinary system
Computed tomography images
Kidney stones
description Renal lithiasis is the pathology that causes nephritic colic, which is one of the most frequent reasons for consultation in emergency medical services. According to the size, location, hardness and number of stones present in the urinary system, usually in the human kidney, it is established to which form of treatment is suitable for the patient. These kidney stones can be analyzed by means of biopsy or imaging modalities such as computed tomography images. This type of images has challenging problems called noise, artifacts and low contrast. In this paper, in order to address these problems, a non-parametric semi-automatic computational technique is developed for detecting kidney stones, present in computed tomography images, using digital image processing techniques based on a smoothing filter and an edge detector. Finally, the size and position of the stones present in the images are calculated and a precision metric is considered to compare the manual segmentation, performed by an urologist, and the one generated by the NPCT, obtaining an excellent correlation. This technique can be useful in the renal lithiasis detection and if it is considering this kind of computational strategy, medical specialists can establish the clinic or surgical actions oriented to address this pathology.
publishDate 2019
dc.date.issued.none.fl_str_mv 2019
dc.date.accessioned.none.fl_str_mv 2020-03-26T21:36:37Z
dc.date.available.none.fl_str_mv 2020-03-26T21:36:37Z
dc.type.eng.fl_str_mv article
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dc.type.driver.eng.fl_str_mv article
dc.identifier.issn.none.fl_str_mv 17426596
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12442/5070
identifier_str_mv 17426596
url https://hdl.handle.net/20.500.12442/5070
dc.language.iso.eng.fl_str_mv eng
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dc.format.mimetype.spa.fl_str_mv pdf
dc.publisher.eng.fl_str_mv IOP Publishing
dc.source.eng.fl_str_mv Journal of Physics: Conference Series
Vol. 1414 (2019)
institution Universidad Simón Bolívar
dc.source.uri.eng.fl_str_mv https://iopscience.iop.org/article/10.1088/1742-6596/1414/1/012019
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spelling Rodríguez-Ibáñez, Rf166c545-1967-4fa3-8726-dd9ea3d63c8bVera, M I4c675edd-c7b6-4fee-87e2-feb90cfc363eVera, M847eada8-99d3-4ff1-a613-ae3f62c30f9eGelvez-Almeida, E55062614-d175-4da1-834a-d7e54dcc92deHuérfano, Y001cc35e-75ac-48b8-9fd0-3c22464ff80fValbuena, O4286f2e0-ce46-49ce-a106-bd00c21a76e9Salazar-Torres, J40a2a6c9-3e39-4994-9b5a-1c6112bd80002020-03-26T21:36:37Z2020-03-26T21:36:37Z201917426596https://hdl.handle.net/20.500.12442/5070Renal lithiasis is the pathology that causes nephritic colic, which is one of the most frequent reasons for consultation in emergency medical services. According to the size, location, hardness and number of stones present in the urinary system, usually in the human kidney, it is established to which form of treatment is suitable for the patient. These kidney stones can be analyzed by means of biopsy or imaging modalities such as computed tomography images. This type of images has challenging problems called noise, artifacts and low contrast. In this paper, in order to address these problems, a non-parametric semi-automatic computational technique is developed for detecting kidney stones, present in computed tomography images, using digital image processing techniques based on a smoothing filter and an edge detector. Finally, the size and position of the stones present in the images are calculated and a precision metric is considered to compare the manual segmentation, performed by an urologist, and the one generated by the NPCT, obtaining an excellent correlation. This technique can be useful in the renal lithiasis detection and if it is considering this kind of computational strategy, medical specialists can establish the clinic or surgical actions oriented to address this pathology.pdfengIOP PublishingAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/http://purl.org/coar/access_right/c_abf2Journal of Physics: Conference SeriesVol. 1414 (2019)https://iopscience.iop.org/article/10.1088/1742-6596/1414/1/012019Renal lithiasisUrinary systemComputed tomography imagesKidney stonesRenal lithiasis detection in uro-computed tomography using a non-parametric techniquearticlearticlehttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Raja A and Ranjani J 2013 Segment based detection and quantification of kidney stones and its symmetric analysis using texture properties based on logical operators with ultrasound scanning International Journal of Computer Applications 975 8887Primak A, McCollough C, Bruesewitz M, Zhang J and Fletcher J 2006 Relationship between noise, dose, and pitch in cardiac multi–detector row ct Radiographics 26 1785Wang G and Vannier M 1994 Stair–step artifacts in three-dimensional helical CT: An experimental study Radiology 191 79Liu J, Wang S and Turkbey E 2015 Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and mser features Medical Physics 42 144Ebrahimi S and Mariano V 2015 Image quality improvement in kidney stone detection on computed tomography images Journal of Image and Graphics 3 40Sujata N, Siti F, Valliappan R and Sundresan P 2018 Automated kidney stone segmentation by seed pixel region growing approach: Initial implementation and results International Journal of Engineering and Technology 7 43Pratt W 2007 Digital image processing (New York: John Wiley & Sons Inc)Saénz F, Vera M, Huérfano Y, Molina V, Martinez L, Vera MI, Salazar W, Gelvez E, Salazar J, Valbuena O, Robles H, Bautista M and Arango J 2018 Brain hematoma computational segmentation Journal of Physics: Conference Series 1126 012071Burden R and Faires D 2010 Numerical analysis (Mexico: CENGAGE Learning)Huérfano Y, Vera M, Mar A and Bravo A 2019 Integrating a gradient–based difference operator with machine learning techniques in right heart segmentation Journal of Physics: Conference Series 1160 012003Dice L 1945 Measures of the amount of ecologic association between species Ecology 26 29Latarjet M and Ruiz A 2004 Anatomía humana (Barcelona: Médica Panamericana)ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf542969https://bonga.unisimon.edu.co/bitstreams/6c8be018-e754-4d7b-acfd-05c83a5f9121/download32847fd6452adb3281e2175d7d30dc29MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805https://bonga.unisimon.edu.co/bitstreams/12870a3d-50a1-4c5b-904d-fa9e6ecae86f/download4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8381https://bonga.unisimon.edu.co/bitstreams/3ff9b61b-252c-42c0-b9b3-2e9543dc8d31/download733bec43a0bf5ade4d97db708e29b185MD53TEXTRenal_lithiasis_detection_UCT.pdf.txtRenal_lithiasis_detection_UCT.pdf.txtExtracted texttext/plain14829https://bonga.unisimon.edu.co/bitstreams/c7a75244-938e-4955-9eed-eff16205c578/download736a596516059544b3acb97268d801b7MD54PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain15358https://bonga.unisimon.edu.co/bitstreams/77071bb4-d3c6-4a0e-af80-b4385542da44/download7bc04271b2d3ad89136eb52867c4e531MD56THUMBNAILRenal_lithiasis_detection_UCT.pdf.jpgRenal_lithiasis_detection_UCT.pdf.jpgGenerated Thumbnailimage/jpeg1298https://bonga.unisimon.edu.co/bitstreams/7a92ae97-fb43-479c-bb67-7ddee28c9068/downloadb5e622c4cb71b568a07778d11bf734c2MD55PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg3343https://bonga.unisimon.edu.co/bitstreams/94bdaa4b-2745-4c44-9171-ea4632dfabdf/download9ec8e83bc19296df75af15514eb9b84fMD5720.500.12442/5070oai:bonga.unisimon.edu.co:20.500.12442/50702024-08-14 21:54:20.343http://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.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