From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Tese |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações do LNCC |
Texto Completo: | https://tede.lncc.br/handle/tede/261 |
Resumo: | Cardiovascular diseases are the principal cause of mortality and morbidity worldwide mostly due to myocardial infarction and stroke. The understanding of the genesis, development and progression of such diseases is key for effective diagnosis, treatment and surgical risk assessment. Notorious advances have been performed in the histological characterization of culprit plaque for such events, although in-vivo techniques for tissue characterization still comprise an extremely active area of research. In this work, a framework is proposed targeting the in-vivo characterization of the arterial wall tissues. The set of methodologies involves: novel image processing methods for medical image enhancement (gating, registration and denoising of high frequency ultrasonic images) and optical flow estimation; detailed mechanical models for coronary arteries; and an efficient data assimilation method for tissue characterization. The thesis is structured in three parts: i) medical image processing; ii) material parameter estimation and iii) medical applications. Particularly, this work makes use of Intravacular Ultrasound (IVUS) as medical image acquisition technique, even though, the second part of the thesis is generic and can be straightforwardly extended to other imaging techniques. In the first part, different methods are presented to enhance and retrieve data of arterial vessel deformations and spatial description of anatomical structures. A novel gating method is proposed to obtain the vessel description at each instant along the cardiac cycle. Due to the intrinsic motion of the sensors during the image acquisition, we propose a registration method that corrects the sensor displacement in the transversal plane of acquisition and along the axis of the vessel. To improve the signal-to-noise ratio of the ultrasound, we propose a denoising method based on the speckle noise (ultrasound characteristic noise) statistics which outperforms classic denoising strategies. Using the three previous methods, we present a methodology to obtain the optical flow of the vessel cross-section during the whole cardiac cycle. In the second part, we scrutinize state-of-the-art literature about the arterial anatomy and mechanical behavior of the arterial wall with particular focus on coronary arteries. Hence, we describe the pathophysiology of the atherosclerosis and the mechanical alterations of the components of the tissues in affected vessels. Then, the tissue characterization problem is addressed by estimating the constitutive parameters of constitutive mechanical models for arterial tissues with a reduced-order unscented Kalman filter. Using the surveyed data and adequate constitutive models, the appropriate setup for the data assimilation problem is studied, and the capabilities of the proposed strategy for tissue estimation are assessed. Then, optical flow techniques are employed to characterize the tissues in-vivo. The third part of the thesis presents a side contribution related to the first part of this work, that is a multimodality comparison for the generation of geometric arterial models from medical images. Specifically, we compare coronary computed tomography angiography (CCTA) versus coronary angiography fused with intravascular ultrasound in terms of geometric descriptors and hemodynamic indexes derived from the geometric models. In such study the gating and registration techniques developed in the first part of the thesis are employed. |
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Blanco, Pablo Javierhttp://lattes.cnpq.br/2207239537360072Feijóo, Raul Antoninohttp://lattes.cnpq.br/2980425786626151Fancello, Eduardo AlbertoCampos, Carlos Augusto Homem de MagalhãesNovotny, Antonio AndréGiraldi, Gilson Antônio06140002702http://lattes.cnpq.br/0851899214244807Maso Talou, Gonzalo Daniel2017-05-04T18:38:32Z2017-03-31MASO TALOU, Gonzalo Daniel. From medical image processing to in-vivo mechanical characterization: a framework based on IVUS studies, 2017, xix, 210f. Tese (Programa de Pós-Graduação em Modelagem Computacional) - Laboratório Nacional de Computação Científica, Petrópolis, 2017.https://tede.lncc.br/handle/tede/261Cardiovascular diseases are the principal cause of mortality and morbidity worldwide mostly due to myocardial infarction and stroke. The understanding of the genesis, development and progression of such diseases is key for effective diagnosis, treatment and surgical risk assessment. Notorious advances have been performed in the histological characterization of culprit plaque for such events, although in-vivo techniques for tissue characterization still comprise an extremely active area of research. In this work, a framework is proposed targeting the in-vivo characterization of the arterial wall tissues. The set of methodologies involves: novel image processing methods for medical image enhancement (gating, registration and denoising of high frequency ultrasonic images) and optical flow estimation; detailed mechanical models for coronary arteries; and an efficient data assimilation method for tissue characterization. The thesis is structured in three parts: i) medical image processing; ii) material parameter estimation and iii) medical applications. Particularly, this work makes use of Intravacular Ultrasound (IVUS) as medical image acquisition technique, even though, the second part of the thesis is generic and can be straightforwardly extended to other imaging techniques. In the first part, different methods are presented to enhance and retrieve data of arterial vessel deformations and spatial description of anatomical structures. A novel gating method is proposed to obtain the vessel description at each instant along the cardiac cycle. Due to the intrinsic motion of the sensors during the image acquisition, we propose a registration method that corrects the sensor displacement in the transversal plane of acquisition and along the axis of the vessel. To improve the signal-to-noise ratio of the ultrasound, we propose a denoising method based on the speckle noise (ultrasound characteristic noise) statistics which outperforms classic denoising strategies. Using the three previous methods, we present a methodology to obtain the optical flow of the vessel cross-section during the whole cardiac cycle. In the second part, we scrutinize state-of-the-art literature about the arterial anatomy and mechanical behavior of the arterial wall with particular focus on coronary arteries. Hence, we describe the pathophysiology of the atherosclerosis and the mechanical alterations of the components of the tissues in affected vessels. Then, the tissue characterization problem is addressed by estimating the constitutive parameters of constitutive mechanical models for arterial tissues with a reduced-order unscented Kalman filter. Using the surveyed data and adequate constitutive models, the appropriate setup for the data assimilation problem is studied, and the capabilities of the proposed strategy for tissue estimation are assessed. Then, optical flow techniques are employed to characterize the tissues in-vivo. The third part of the thesis presents a side contribution related to the first part of this work, that is a multimodality comparison for the generation of geometric arterial models from medical images. Specifically, we compare coronary computed tomography angiography (CCTA) versus coronary angiography fused with intravascular ultrasound in terms of geometric descriptors and hemodynamic indexes derived from the geometric models. In such study the gating and registration techniques developed in the first part of the thesis are employed.As doenças cardiovasculares são a principal causa de mortalidade e morbidade em todo o mundo, principalmente devido a acidentes vasculares tais como infarto de miocárdio e acidente cerebro-vascular. O entendimento da gênese, progressão e comportamento de tais doenças é fundamental para um eficaz diagnóstico, tratamento e avaliação de risco cirúrgico. Grandes avanços foram realizados na caracterização histológica da placa vulnerável que conduz a acidentes vasculares, embora as técnicas in-vivo para a visualização da mesma ainda constituam uma área de pesquiza extremamente activa. Neste trabalho é proposta um metodologia para estudar a caracterização in-vivo dos tecidos da parede arterial. Esta metodologia envolve: novos métodos de aprimoramento de imagens médicas (gating, registro e redução de ruído para imagens de ultrassom de alta frequência) e estimativa de fluxo ótico; modelos mecânicos detalhados para artérias coronárias; e um método eficiente de assimilação de dados para a caracterização de tecidos. A tese é dividida em três partes: i) processamento de imagens médicas; ii) estimação de parâmetros de material e iii) aplicações médicas. Particularmente, este trabalho foca-se no uso do ultrassom intravascular (IVUS) como técnica de imagens médicas, embora a segunda parte do manuscrito é suficientemente genérica para ser estendida para outros tipos de imagens médicas. Na primeira parte, são apresentados diferentes métodos para melhorar e recuperar de medidas de deformações e descrição espacial das estruturas anatômicas dos vasos arteriais. Propõe-se um novo método de gating para extrair a descrição do vaso em cada instante do ciclo cardíaco. Devido ao movimento intrínseco dos sensores durante a aquisição da imagem de ultrassom, propomos um método de registro que corrige este deslocamento no plano transversal e no eixo axial de aquisição. Para melhorar a relação sinal-ruído das imagens geradas, propõe-se um método de redução de ruído baseado na estatística do ruído ``speckle'' (ruído intrínseco do ultrassom), que supera as estratégias clássicas de redução de ruído presentes na literatura. Usando os três métodos anteriores, apresentamos uma metodologia para estimar o fluxo óptico da seção transversal do vaso durante o ciclo cardíaco. Na segunda parte, apresentamos um resumo do estado da arte sobre a anatomia arterial e o comportamento mecânico da parede arterial, com especial ênfase nas artérias coronárias. Assim, descrevemos a fisiopatologia da aterosclerose e as alterações mecânicas nos tecidos dos vasos afetados. Em seguida, o problema de caracterização de tecidos é abordado, estimando os parâmetros constitutivos de modelos mecânicos para tecidos arteriais via filtros de Kalman. Utilizando dados experimentais de especímens ex-vivo e modelos constitutivos apropriados, estuda-se a configuração do filtro de Kalman e avalia-se a capacidade da estratégia proposta para a estimação de tecidos. Por último, são empregadas técnicas de fluxo óptico desenvolvidas na primeira parte, para abordar a caracterização dos tecidos in-vivo. A terceira parte da tese apresenta uma contribuição obtida com as técnicas desenvolvidas na primeira parte deste trabalho. Realiza-se uma comparação multimodal para a geração de modelos geomêtricos arteriais a partir de imagens médicas. Especificamente, comparamos a tomografia coronariana computadorizada (CCTA) versus a angiografia coronariana fundida com ultrassom intravascular em termos de descritores geométricos e índices hemodinâmicos derivados dos modelos geomêtricos. Neste estudo são empregadas técnicas de gating e registro para obter uma correta descrição geométrica dos vasos.Submitted by Maria Cristina (library@lncc.br) on 2017-05-04T18:38:09Z No. of bitstreams: 1 ThesisMasoTalou_Oficial_simpleFace.pdf: 68280242 bytes, checksum: 9e68eebcd1ef31f7a60de5be481eda3b (MD5)Approved for entry into archive by Maria Cristina (library@lncc.br) on 2017-05-04T18:38:20Z (GMT) No. of bitstreams: 1 ThesisMasoTalou_Oficial_simpleFace.pdf: 68280242 bytes, checksum: 9e68eebcd1ef31f7a60de5be481eda3b (MD5)Made available in DSpace on 2017-05-04T18:38:32Z (GMT). No. of bitstreams: 1 ThesisMasoTalou_Oficial_simpleFace.pdf: 68280242 bytes, checksum: 9e68eebcd1ef31f7a60de5be481eda3b (MD5) Previous issue date: 2017-03-31Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ)application/pdfhttp://tede-server.lncc.br:8080/retrieve/852/ThesisMasoTalou_Oficial_simpleFace.pdf.jpgporLaboratório Nacional de Computação CientíficaPrograma de Pós-Graduação em Modelagem ComputacionalLNCCBrasilCoordenação de Pós-Graduação e Aperfeiçoamento (COPGA)Processamento de imagensDoenças cardiovasculares - DiagnósticoCardiovascular diseases - DiagnosisImage processingCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO::MODELOS ANALITICOS E DE SIMULACAOCNPQ::CIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CARDIOLOGIAFrom medical image processing to in-vivo mechanical characterization : a framework based on IVUS studiesDesde o processamento de imagens médicas até a characterização in-vivo das propriedades mecânicas: um framework baseado em estudos IVUS.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações do LNCCinstname:Laboratório Nacional de Computação Científica (LNCC)instacron:LNCCLICENSElicense.txtlicense.txttext/plain; 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dc.title.por.fl_str_mv |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
dc.title.alternative.por.fl_str_mv |
Desde o processamento de imagens médicas até a characterização in-vivo das propriedades mecânicas: um framework baseado em estudos IVUS. |
title |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
spellingShingle |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies Maso Talou, Gonzalo Daniel Processamento de imagens Doenças cardiovasculares - Diagnóstico Cardiovascular diseases - Diagnosis Image processing CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO::MODELOS ANALITICOS E DE SIMULACAO CNPQ::CIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CARDIOLOGIA |
title_short |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
title_full |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
title_fullStr |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
title_full_unstemmed |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
title_sort |
From medical image processing to in-vivo mechanical characterization : a framework based on IVUS studies |
author |
Maso Talou, Gonzalo Daniel |
author_facet |
Maso Talou, Gonzalo Daniel |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Blanco, Pablo Javier |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/2207239537360072 |
dc.contributor.advisor2.fl_str_mv |
Feijóo, Raul Antonino |
dc.contributor.advisor2Lattes.fl_str_mv |
http://lattes.cnpq.br/2980425786626151 |
dc.contributor.referee1.fl_str_mv |
Fancello, Eduardo Alberto |
dc.contributor.referee2.fl_str_mv |
Campos, Carlos Augusto Homem de Magalhães |
dc.contributor.referee3.fl_str_mv |
Novotny, Antonio André |
dc.contributor.referee4.fl_str_mv |
Giraldi, Gilson Antônio |
dc.contributor.authorID.fl_str_mv |
06140002702 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0851899214244807 |
dc.contributor.author.fl_str_mv |
Maso Talou, Gonzalo Daniel |
contributor_str_mv |
Blanco, Pablo Javier Feijóo, Raul Antonino Fancello, Eduardo Alberto Campos, Carlos Augusto Homem de Magalhães Novotny, Antonio André Giraldi, Gilson Antônio |
dc.subject.por.fl_str_mv |
Processamento de imagens Doenças cardiovasculares - Diagnóstico Cardiovascular diseases - Diagnosis |
topic |
Processamento de imagens Doenças cardiovasculares - Diagnóstico Cardiovascular diseases - Diagnosis Image processing CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO::MODELOS ANALITICOS E DE SIMULACAO CNPQ::CIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CARDIOLOGIA |
dc.subject.eng.fl_str_mv |
Image processing |
dc.subject.cnpq.fl_str_mv |
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO::MODELOS ANALITICOS E DE SIMULACAO CNPQ::CIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CARDIOLOGIA |
description |
Cardiovascular diseases are the principal cause of mortality and morbidity worldwide mostly due to myocardial infarction and stroke. The understanding of the genesis, development and progression of such diseases is key for effective diagnosis, treatment and surgical risk assessment. Notorious advances have been performed in the histological characterization of culprit plaque for such events, although in-vivo techniques for tissue characterization still comprise an extremely active area of research. In this work, a framework is proposed targeting the in-vivo characterization of the arterial wall tissues. The set of methodologies involves: novel image processing methods for medical image enhancement (gating, registration and denoising of high frequency ultrasonic images) and optical flow estimation; detailed mechanical models for coronary arteries; and an efficient data assimilation method for tissue characterization. The thesis is structured in three parts: i) medical image processing; ii) material parameter estimation and iii) medical applications. Particularly, this work makes use of Intravacular Ultrasound (IVUS) as medical image acquisition technique, even though, the second part of the thesis is generic and can be straightforwardly extended to other imaging techniques. In the first part, different methods are presented to enhance and retrieve data of arterial vessel deformations and spatial description of anatomical structures. A novel gating method is proposed to obtain the vessel description at each instant along the cardiac cycle. Due to the intrinsic motion of the sensors during the image acquisition, we propose a registration method that corrects the sensor displacement in the transversal plane of acquisition and along the axis of the vessel. To improve the signal-to-noise ratio of the ultrasound, we propose a denoising method based on the speckle noise (ultrasound characteristic noise) statistics which outperforms classic denoising strategies. Using the three previous methods, we present a methodology to obtain the optical flow of the vessel cross-section during the whole cardiac cycle. In the second part, we scrutinize state-of-the-art literature about the arterial anatomy and mechanical behavior of the arterial wall with particular focus on coronary arteries. Hence, we describe the pathophysiology of the atherosclerosis and the mechanical alterations of the components of the tissues in affected vessels. Then, the tissue characterization problem is addressed by estimating the constitutive parameters of constitutive mechanical models for arterial tissues with a reduced-order unscented Kalman filter. Using the surveyed data and adequate constitutive models, the appropriate setup for the data assimilation problem is studied, and the capabilities of the proposed strategy for tissue estimation are assessed. Then, optical flow techniques are employed to characterize the tissues in-vivo. The third part of the thesis presents a side contribution related to the first part of this work, that is a multimodality comparison for the generation of geometric arterial models from medical images. Specifically, we compare coronary computed tomography angiography (CCTA) versus coronary angiography fused with intravascular ultrasound in terms of geometric descriptors and hemodynamic indexes derived from the geometric models. In such study the gating and registration techniques developed in the first part of the thesis are employed. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-05-04T18:38:32Z |
dc.date.issued.fl_str_mv |
2017-03-31 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
MASO TALOU, Gonzalo Daniel. From medical image processing to in-vivo mechanical characterization: a framework based on IVUS studies, 2017, xix, 210f. Tese (Programa de Pós-Graduação em Modelagem Computacional) - Laboratório Nacional de Computação Científica, Petrópolis, 2017. |
dc.identifier.uri.fl_str_mv |
https://tede.lncc.br/handle/tede/261 |
identifier_str_mv |
MASO TALOU, Gonzalo Daniel. From medical image processing to in-vivo mechanical characterization: a framework based on IVUS studies, 2017, xix, 210f. Tese (Programa de Pós-Graduação em Modelagem Computacional) - Laboratório Nacional de Computação Científica, Petrópolis, 2017. |
url |
https://tede.lncc.br/handle/tede/261 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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Laboratório Nacional de Computação Científica |
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