Study of cervical cancer through fractals and a method of clustering based on quantum mechanics

Tumor growth in the cervix is a complex process. Understanding this phenomena is quite relevant in order to establish proper diagnosis and therapy strategies and a possible startpoint is to evaluate its complexity through the scaling analysis, which define the tumor growth geometry. In this work, tu...

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Autores:
Torres Hoyos, Francisco José
Martín-Landrove, M.
Baena Navarro, Rubén Enrique
Vergara Villadiego, Juan Raul
Cardenas, J. C.
Tipo de recurso:
Article of journal
Fecha de publicación:
2019
Institución:
Universidad Cooperativa de Colombia
Repositorio:
Repositorio UCC
Idioma:
OAI Identifier:
oai:repository.ucc.edu.co:20.500.12494/41424
Acceso en línea:
https://doi.org/10.1016/j.fluid.2012.02.009
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062487040&doi=10.1088%2f1742-6596%2f1160%2f1%2f012019&partnerID=40&md5=6e2018f40b33214f2223fe5c736f2276
https://hdl.handle.net/20.500.12494/41424
Palabra clave:
Algorithms
Diagnosis
Diseases
Fractal dimension
Fractals
Image enhancement
Magnetic resonance
Quantum theory
Tumors
05
45
Df
68
35
Ct
Cervix
K-means
Local roughness
K-means clustering
Article
cancer staging
clinical protocol
cluster analysis
contrast enhancement
controlled study
female
fractal analysis
human
image analysis
image processing
image segmentation
in vivo study
major clinical study
nuclear magnetic resonance imaging
oncological parameters
priority journal
quantum mechanics
three dimensional imaging
tumor growth
tumor volume
uterine cervix adenocarcinoma
uterine cervix cancer
adenocarcinoma
algorithm
cluster analysis
computer assisted diagnosis
diagnostic imaging
fractal analysis
pathology
procedures
quantum theory
squamous cell carcinoma
uterine cervix tumor
Adenocarcinoma
Algorithms
Carcinoma
Squamous Cell
Cluster Analysis
Female
Fractals
Humans
Image Interpretation
Computer-Assisted
Imaging
Three-Dimensional
Magn
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closedAccess
License
http://purl.org/coar/access_right/c_14cb
id COOPER2_4bb6a44dcd34205172e9fa7470c8141f
oai_identifier_str oai:repository.ucc.edu.co:20.500.12494/41424
network_acronym_str COOPER2
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repository_id_str
spelling Torres Hoyos, Francisco JoséMartín-Landrove, M.Baena Navarro, Rubén EnriqueVergara Villadiego, Juan RaulCardenas, J. C.2021-12-16T22:15:30Z2021-12-16T22:15:30Z2019https://doi.org/10.1016/j.fluid.2012.02.009https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062487040&doi=10.1088%2f1742-6596%2f1160%2f1%2f012019&partnerID=40&md5=6e2018f40b33214f2223fe5c736f227609698043https://hdl.handle.net/20.500.12494/41424Hoyos FT,Martín M,Baena R,Vergara J,Cardenas JC. Study of cervical cancer through fractals and a method of clustering based on quantum mechanics. Appl Radiat Isot. 2019. 150. p. 182-191. .Tumor growth in the cervix is a complex process. Understanding this phenomena is quite relevant in order to establish proper diagnosis and therapy strategies and a possible startpoint is to evaluate its complexity through the scaling analysis, which define the tumor growth geometry. In this work, tumor interface from primary tumors of squamous cells and adenocarcinomas for cervical cancer were extracted. Fractal dimension and local roughness exponent (Barabási and Stanley (1996)), aloc, were calculated to characterize the in vivo 3-D tumor growth. Image acquisition was carried out according to the standard protocol used for cervical cancer radiotherapy, i.e., axial, magnetic resonance T1 - weighted contrast enhanced images comprising the cervix volume for image registration. Image processing was carried out by a classification scheme based on quantum clustering algorithm (Mussa et al. (2015))combined with the application of the K-means procedure upon contrasted images (Demirkaya et al. (2008)). The results show significant variations of the parameters depending on the tumor stage and its histological origin. © 20190000-0001-5055-6515ruben.baena@campusucc.edu.co191-182Elsevier LtdAlgorithmsDiagnosisDiseasesFractal dimensionFractalsImage enhancementMagnetic resonanceQuantum theoryTumors0545Df6835CtCervixK-meansLocal roughnessK-means clusteringArticlecancer stagingclinical protocolcluster analysiscontrast enhancementcontrolled studyfemalefractal analysishumanimage analysisimage processingimage segmentationin vivo studymajor clinical studynuclear magnetic resonance imagingoncological parameterspriority journalquantum mechanicsthree dimensional imagingtumor growthtumor volumeuterine cervix adenocarcinomauterine cervix canceradenocarcinomaalgorithmcluster analysiscomputer assisted diagnosisdiagnostic imagingfractal analysispathologyproceduresquantum theorysquamous cell carcinomauterine cervix tumorAdenocarcinomaAlgorithmsCarcinomaSquamous CellCluster AnalysisFemaleFractalsHumansImage InterpretationComputer-AssistedImagingThree-DimensionalMagnStudy of cervical cancer through fractals and a method of clustering based on quantum mechanicsArtículohttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionAPPL RADIAT ISOTOPESinfo:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbPublication20.500.12494/41424oai:repository.ucc.edu.co:20.500.12494/414242024-08-20 16:16:25.552metadata.onlyhttps://repository.ucc.edu.coRepositorio Institucional Universidad Cooperativa de Colombiabdigital@metabiblioteca.com
dc.title.spa.fl_str_mv Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
title Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
spellingShingle Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
Algorithms
Diagnosis
Diseases
Fractal dimension
Fractals
Image enhancement
Magnetic resonance
Quantum theory
Tumors
05
45
Df
68
35
Ct
Cervix
K-means
Local roughness
K-means clustering
Article
cancer staging
clinical protocol
cluster analysis
contrast enhancement
controlled study
female
fractal analysis
human
image analysis
image processing
image segmentation
in vivo study
major clinical study
nuclear magnetic resonance imaging
oncological parameters
priority journal
quantum mechanics
three dimensional imaging
tumor growth
tumor volume
uterine cervix adenocarcinoma
uterine cervix cancer
adenocarcinoma
algorithm
cluster analysis
computer assisted diagnosis
diagnostic imaging
fractal analysis
pathology
procedures
quantum theory
squamous cell carcinoma
uterine cervix tumor
Adenocarcinoma
Algorithms
Carcinoma
Squamous Cell
Cluster Analysis
Female
Fractals
Humans
Image Interpretation
Computer-Assisted
Imaging
Three-Dimensional
Magn
title_short Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
title_full Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
title_fullStr Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
title_full_unstemmed Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
title_sort Study of cervical cancer through fractals and a method of clustering based on quantum mechanics
dc.creator.fl_str_mv Torres Hoyos, Francisco José
Martín-Landrove, M.
Baena Navarro, Rubén Enrique
Vergara Villadiego, Juan Raul
Cardenas, J. C.
dc.contributor.author.none.fl_str_mv Torres Hoyos, Francisco José
Martín-Landrove, M.
Baena Navarro, Rubén Enrique
Vergara Villadiego, Juan Raul
Cardenas, J. C.
dc.subject.spa.fl_str_mv Algorithms
Diagnosis
Diseases
Fractal dimension
Fractals
Image enhancement
Magnetic resonance
Quantum theory
Tumors
05
45
Df
68
35
Ct
Cervix
K-means
Local roughness
K-means clustering
Article
cancer staging
clinical protocol
cluster analysis
contrast enhancement
controlled study
female
fractal analysis
human
image analysis
image processing
image segmentation
in vivo study
major clinical study
nuclear magnetic resonance imaging
oncological parameters
priority journal
quantum mechanics
three dimensional imaging
tumor growth
tumor volume
uterine cervix adenocarcinoma
uterine cervix cancer
adenocarcinoma
algorithm
cluster analysis
computer assisted diagnosis
diagnostic imaging
fractal analysis
pathology
procedures
quantum theory
squamous cell carcinoma
uterine cervix tumor
Adenocarcinoma
Algorithms
Carcinoma
Squamous Cell
Cluster Analysis
Female
Fractals
Humans
Image Interpretation
Computer-Assisted
Imaging
Three-Dimensional
Magn
topic Algorithms
Diagnosis
Diseases
Fractal dimension
Fractals
Image enhancement
Magnetic resonance
Quantum theory
Tumors
05
45
Df
68
35
Ct
Cervix
K-means
Local roughness
K-means clustering
Article
cancer staging
clinical protocol
cluster analysis
contrast enhancement
controlled study
female
fractal analysis
human
image analysis
image processing
image segmentation
in vivo study
major clinical study
nuclear magnetic resonance imaging
oncological parameters
priority journal
quantum mechanics
three dimensional imaging
tumor growth
tumor volume
uterine cervix adenocarcinoma
uterine cervix cancer
adenocarcinoma
algorithm
cluster analysis
computer assisted diagnosis
diagnostic imaging
fractal analysis
pathology
procedures
quantum theory
squamous cell carcinoma
uterine cervix tumor
Adenocarcinoma
Algorithms
Carcinoma
Squamous Cell
Cluster Analysis
Female
Fractals
Humans
Image Interpretation
Computer-Assisted
Imaging
Three-Dimensional
Magn
description Tumor growth in the cervix is a complex process. Understanding this phenomena is quite relevant in order to establish proper diagnosis and therapy strategies and a possible startpoint is to evaluate its complexity through the scaling analysis, which define the tumor growth geometry. In this work, tumor interface from primary tumors of squamous cells and adenocarcinomas for cervical cancer were extracted. Fractal dimension and local roughness exponent (Barabási and Stanley (1996)), aloc, were calculated to characterize the in vivo 3-D tumor growth. Image acquisition was carried out according to the standard protocol used for cervical cancer radiotherapy, i.e., axial, magnetic resonance T1 - weighted contrast enhanced images comprising the cervix volume for image registration. Image processing was carried out by a classification scheme based on quantum clustering algorithm (Mussa et al. (2015))combined with the application of the K-means procedure upon contrasted images (Demirkaya et al. (2008)). The results show significant variations of the parameters depending on the tumor stage and its histological origin. © 2019
publishDate 2019
dc.date.issued.none.fl_str_mv 2019
dc.date.accessioned.none.fl_str_mv 2021-12-16T22:15:30Z
dc.date.available.none.fl_str_mv 2021-12-16T22:15:30Z
dc.type.none.fl_str_mv Artículo
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coarversion.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.none.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1016/j.fluid.2012.02.009
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062487040&doi=10.1088%2f1742-6596%2f1160%2f1%2f012019&partnerID=40&md5=6e2018f40b33214f2223fe5c736f2276
dc.identifier.issn.spa.fl_str_mv 09698043
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12494/41424
dc.identifier.bibliographicCitation.spa.fl_str_mv Hoyos FT,Martín M,Baena R,Vergara J,Cardenas JC. Study of cervical cancer through fractals and a method of clustering based on quantum mechanics. Appl Radiat Isot. 2019. 150. p. 182-191. .
url https://doi.org/10.1016/j.fluid.2012.02.009
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062487040&doi=10.1088%2f1742-6596%2f1160%2f1%2f012019&partnerID=40&md5=6e2018f40b33214f2223fe5c736f2276
https://hdl.handle.net/20.500.12494/41424
identifier_str_mv 09698043
Hoyos FT,Martín M,Baena R,Vergara J,Cardenas JC. Study of cervical cancer through fractals and a method of clustering based on quantum mechanics. Appl Radiat Isot. 2019. 150. p. 182-191. .
dc.relation.ispartofjournal.spa.fl_str_mv APPL RADIAT ISOTOPES
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/closedAccess
dc.rights.coar.none.fl_str_mv http://purl.org/coar/access_right/c_14cb
eu_rights_str_mv closedAccess
rights_invalid_str_mv http://purl.org/coar/access_right/c_14cb
dc.format.extent.spa.fl_str_mv 191-182
dc.publisher.spa.fl_str_mv Elsevier Ltd
institution Universidad Cooperativa de Colombia
repository.name.fl_str_mv Repositorio Institucional Universidad Cooperativa de Colombia
repository.mail.fl_str_mv bdigital@metabiblioteca.com
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