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...
- Autores:
-
Torres Hoyos, Francisco José
Martín-Landrove, M.
Baena Navarro, Rubén Enrique
Vergara Villadiego, Juan
Cardenas, J. C.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2023
- Institución:
- Universidad Cooperativa de Colombia
- Repositorio:
- Repositorio UCC
- Idioma:
- OAI Identifier:
- oai:repository.ucc.edu.co:20.500.12494/51057
- Acceso en línea:
- https://doi.org/10.1016/j.apradiso.2019.05.011
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066450668&doi=10.1016%2fj.apradiso.2019.05.011&partnerID=40&md5=b71bab8fe0dd1ea08fe409f254ef699c
https://hdl.handle.net/20.500.12494/51057
- Palabra clave:
- 05.45.DF
68.35.CT
ADENOCARCINOMA
ALGORITHM
ALGORITHMS
ARTICLE
CANCER STAGING
CARCINOMA, SQUAMOUS CELL
CERVIX
CLINICAL PROTOCOL
CLUSTER ANALYSIS
COMPUTER ASSISTED DIAGNOSIS
CONTRAST ENHANCEMENT
CONTROLLED STUDY
DIAGNOSIS
DIAGNOSTIC IMAGING
DISEASES
FEMALE
FRACTAL ANALYSIS
FRACTAL DIMENSION
FRACTALS
HUMAN
HUMANS
IMAGE ANALYSIS
IMAGE ENHANCEMENT
IMAGE INTERPRETATION, COMPUTER-ASSISTED
IMAGE PROCESSING
IMAGE SEGMENTATION
IMAGING, THREE-DIMENSIONAL
IN VIVO STUDY
K-MEANS
K-MEANS CLUSTERING
LOCAL ROUGHNESS
MAGN
MAGNETIC RESONANCE
MAJOR CLINICAL STUDY
NUCLEAR MAGNETIC RESONANCE IMAGING
ONCOLOGICAL PARAMETERS
PATHOLOGY
PRIORITY JOURNAL
PROCEDURES
QUANTUM MECHANICS
QUANTUM THEORY
SQUAMOUS CELL CARCINOMA
THREE DIMENSIONAL IMAGING
TUMOR GROWTH
TUMOR VOLUME
TUMORS
UTERINE CERVIX ADENOCARCINOMA
UTERINE CERVIX CANCER
UTERINE CERVIX TUMOR
- Rights
- openAccess
- License
- http://purl.org/coar/access_right/c_abf2
id |
COOPER2_d73a1828822c2659e8af4a4465bb3353 |
---|---|
oai_identifier_str |
oai:repository.ucc.edu.co:20.500.12494/51057 |
network_acronym_str |
COOPER2 |
network_name_str |
Repositorio UCC |
repository_id_str |
|
spelling |
Torres Hoyos, Francisco JoséMartín-Landrove, M.Baena Navarro, Rubén EnriqueVergara Villadiego, JuanCardenas, J. C.2023-05-24T16:32:15Z2023-05-24T16:32:15Z01/01/2019https://doi.org/10.1016/j.apradiso.2019.05.011https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066450668&doi=10.1016%2fj.apradiso.2019.05.011&partnerID=40&md5=b71bab8fe0dd1ea08fe409f254ef699c09698043https://hdl.handle.net/20.500.12494/51057Torres Hoyos Francisco,Martín-Landrove M.,Baena Navarro Ruben enrique,Vergara Villadiego Juan,Cardenas J.C..Study of cervical cancer through fractals and a method of clustering based on quantum mechanics.APPL RADIAT ISOTOPES. 2019. 150. ():p. 182-191Tumor 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. © 2019ruben.baena@campusucc.edu.co182-191Elsevier Ltd05.45.DF68.35.CTADENOCARCINOMAALGORITHMALGORITHMSARTICLECANCER STAGINGCARCINOMA, SQUAMOUS CELLCERVIXCLINICAL PROTOCOLCLUSTER ANALYSISCOMPUTER ASSISTED DIAGNOSISCONTRAST ENHANCEMENTCONTROLLED STUDYDIAGNOSISDIAGNOSTIC IMAGINGDISEASESFEMALEFRACTAL ANALYSISFRACTAL DIMENSIONFRACTALSHUMANHUMANSIMAGE ANALYSISIMAGE ENHANCEMENTIMAGE INTERPRETATION, COMPUTER-ASSISTEDIMAGE PROCESSINGIMAGE SEGMENTATIONIMAGING, THREE-DIMENSIONALIN VIVO STUDYK-MEANSK-MEANS CLUSTERINGLOCAL ROUGHNESSMAGNMAGNETIC RESONANCEMAJOR CLINICAL STUDYNUCLEAR MAGNETIC RESONANCE IMAGINGONCOLOGICAL PARAMETERSPATHOLOGYPRIORITY JOURNALPROCEDURESQUANTUM MECHANICSQUANTUM THEORYSQUAMOUS CELL CARCINOMATHREE DIMENSIONAL IMAGINGTUMOR GROWTHTUMOR VOLUMETUMORSUTERINE CERVIX ADENOCARCINOMAUTERINE CERVIX CANCERUTERINE CERVIX TUMORStudy 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/openAccesshttp://purl.org/coar/access_right/c_abf2Publication20.500.12494/51057oai:repository.ucc.edu.co:20.500.12494/510572024-08-20 16:21:22.654metadata.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 05.45.DF 68.35.CT ADENOCARCINOMA ALGORITHM ALGORITHMS ARTICLE CANCER STAGING CARCINOMA, SQUAMOUS CELL CERVIX CLINICAL PROTOCOL CLUSTER ANALYSIS COMPUTER ASSISTED DIAGNOSIS CONTRAST ENHANCEMENT CONTROLLED STUDY DIAGNOSIS DIAGNOSTIC IMAGING DISEASES FEMALE FRACTAL ANALYSIS FRACTAL DIMENSION FRACTALS HUMAN HUMANS IMAGE ANALYSIS IMAGE ENHANCEMENT IMAGE INTERPRETATION, COMPUTER-ASSISTED IMAGE PROCESSING IMAGE SEGMENTATION IMAGING, THREE-DIMENSIONAL IN VIVO STUDY K-MEANS K-MEANS CLUSTERING LOCAL ROUGHNESS MAGN MAGNETIC RESONANCE MAJOR CLINICAL STUDY NUCLEAR MAGNETIC RESONANCE IMAGING ONCOLOGICAL PARAMETERS PATHOLOGY PRIORITY JOURNAL PROCEDURES QUANTUM MECHANICS QUANTUM THEORY SQUAMOUS CELL CARCINOMA THREE DIMENSIONAL IMAGING TUMOR GROWTH TUMOR VOLUME TUMORS UTERINE CERVIX ADENOCARCINOMA UTERINE CERVIX CANCER UTERINE CERVIX TUMOR |
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 Cardenas, J. C. |
dc.contributor.author.none.fl_str_mv |
Torres Hoyos, Francisco José Martín-Landrove, M. Baena Navarro, Rubén Enrique Vergara Villadiego, Juan Cardenas, J. C. |
dc.subject.spa.fl_str_mv |
05.45.DF 68.35.CT ADENOCARCINOMA ALGORITHM ALGORITHMS ARTICLE CANCER STAGING CARCINOMA, SQUAMOUS CELL CERVIX CLINICAL PROTOCOL CLUSTER ANALYSIS COMPUTER ASSISTED DIAGNOSIS CONTRAST ENHANCEMENT CONTROLLED STUDY DIAGNOSIS DIAGNOSTIC IMAGING DISEASES FEMALE FRACTAL ANALYSIS FRACTAL DIMENSION FRACTALS HUMAN HUMANS IMAGE ANALYSIS IMAGE ENHANCEMENT IMAGE INTERPRETATION, COMPUTER-ASSISTED IMAGE PROCESSING IMAGE SEGMENTATION IMAGING, THREE-DIMENSIONAL IN VIVO STUDY K-MEANS K-MEANS CLUSTERING LOCAL ROUGHNESS MAGN MAGNETIC RESONANCE MAJOR CLINICAL STUDY NUCLEAR MAGNETIC RESONANCE IMAGING ONCOLOGICAL PARAMETERS PATHOLOGY PRIORITY JOURNAL PROCEDURES QUANTUM MECHANICS QUANTUM THEORY SQUAMOUS CELL CARCINOMA THREE DIMENSIONAL IMAGING TUMOR GROWTH TUMOR VOLUME TUMORS UTERINE CERVIX ADENOCARCINOMA UTERINE CERVIX CANCER UTERINE CERVIX TUMOR |
topic |
05.45.DF 68.35.CT ADENOCARCINOMA ALGORITHM ALGORITHMS ARTICLE CANCER STAGING CARCINOMA, SQUAMOUS CELL CERVIX CLINICAL PROTOCOL CLUSTER ANALYSIS COMPUTER ASSISTED DIAGNOSIS CONTRAST ENHANCEMENT CONTROLLED STUDY DIAGNOSIS DIAGNOSTIC IMAGING DISEASES FEMALE FRACTAL ANALYSIS FRACTAL DIMENSION FRACTALS HUMAN HUMANS IMAGE ANALYSIS IMAGE ENHANCEMENT IMAGE INTERPRETATION, COMPUTER-ASSISTED IMAGE PROCESSING IMAGE SEGMENTATION IMAGING, THREE-DIMENSIONAL IN VIVO STUDY K-MEANS K-MEANS CLUSTERING LOCAL ROUGHNESS MAGN MAGNETIC RESONANCE MAJOR CLINICAL STUDY NUCLEAR MAGNETIC RESONANCE IMAGING ONCOLOGICAL PARAMETERS PATHOLOGY PRIORITY JOURNAL PROCEDURES QUANTUM MECHANICS QUANTUM THEORY SQUAMOUS CELL CARCINOMA THREE DIMENSIONAL IMAGING TUMOR GROWTH TUMOR VOLUME TUMORS UTERINE CERVIX ADENOCARCINOMA UTERINE CERVIX CANCER UTERINE CERVIX TUMOR |
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 |
2023 |
dc.date.issued.none.fl_str_mv |
01/01/2019 |
dc.date.accessioned.none.fl_str_mv |
2023-05-24T16:32:15Z |
dc.date.available.none.fl_str_mv |
2023-05-24T16:32:15Z |
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.apradiso.2019.05.011 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066450668&doi=10.1016%2fj.apradiso.2019.05.011&partnerID=40&md5=b71bab8fe0dd1ea08fe409f254ef699c |
dc.identifier.issn.spa.fl_str_mv |
09698043 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12494/51057 |
dc.identifier.bibliographicCitation.spa.fl_str_mv |
Torres Hoyos Francisco,Martín-Landrove M.,Baena Navarro Ruben enrique,Vergara Villadiego Juan,Cardenas J.C..Study of cervical cancer through fractals and a method of clustering based on quantum mechanics.APPL RADIAT ISOTOPES. 2019. 150. ():p. 182-191 |
url |
https://doi.org/10.1016/j.apradiso.2019.05.011 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85066450668&doi=10.1016%2fj.apradiso.2019.05.011&partnerID=40&md5=b71bab8fe0dd1ea08fe409f254ef699c https://hdl.handle.net/20.500.12494/51057 |
identifier_str_mv |
09698043 Torres Hoyos Francisco,Martín-Landrove M.,Baena Navarro Ruben enrique,Vergara Villadiego Juan,Cardenas J.C..Study of cervical cancer through fractals and a method of clustering based on quantum mechanics.APPL RADIAT ISOTOPES. 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/openAccess |
dc.rights.coar.none.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.format.extent.spa.fl_str_mv |
182-191 |
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 |
_version_ |
1814247142792888320 |