{"id":91688,"date":"2018-03-11T10:10:31","date_gmt":"2018-03-11T10:10:31","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/microwave-medical-imaging-using-level-set-techniques\/"},"modified":"2018-03-11T10:10:31","modified_gmt":"2018-03-11T10:10:31","slug":"microwave-medical-imaging-using-level-set-techniques","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/simulacion\/microwave-medical-imaging-using-level-set-techniques\/","title":{"rendered":"Microwave medical imaging using level set techniques"},"content":{"rendered":"

Tesis doctoral de Natalia Irishina <\/strong><\/h2>\n

El c\u00e1ncer de mama es una de las enfermedades que causan una mayor mortalidad entre las mujeres. Se estima que, solo en europa, una mujer es diagnosticada de esta enfermedad cada 2 minutos y medio, y que una muere cada 7 minutos y medio. Para su cura es fundamental la detecci\u00f3n temprana de los peque\u00f1os tumores. La t\u00e9cnica de referencia, la mamograf\u00eda, es una imagen de rayos x de la mama comprimida. Sin embargo, un 15% de los tumores malignos no detectan, y los falsos positivos alcanzan 13%. Adem\u00e1s, rayos x es la radiaci\u00f3n potencialmente peligrosa y el procedimiento es poco confortable. Otras t\u00e9cnicas alternativas se est\u00e1n estudiando para el diagnostico no invasivo y de bajo coste. Entre ellas, destacan la tomograf\u00eda de \u00f3ptica difusa, la tomograf\u00eda de impedancia el\u00e9ctrica y las im\u00e1genes de microondas. en esta tesis se propone un algoritmo num\u00e9rico dise\u00f1ado para la detecci\u00f3n y caracterizaci\u00f3n de peque\u00f1os tumores usando microondas. La idea consiste en iluminar la mama con radiaci\u00f3n de frecuencias del orden de unos pocos ghz, y reconstruir las im\u00e1genes del interior a partir de las se\u00f1ales que se recogen en la superficie de la mama. La reconstrucci\u00f3n de estas im\u00e1genes supone la resoluci\u00f3n de un proceso inverso en donde se minimiza la diferencia de las se\u00f1ales medidas y de las simuladas con el modelo de mama propuesto (que incluye el posible tumor). Para ello aplicamos t\u00e9cnicas novedosas de conjunto de nivel que permiten la representaci\u00f3n impl\u00edcita de la mama, y suponen adem\u00e1s una regularizaci\u00f3n impl\u00edcita que estabiliza la resoluci\u00f3n del problema inverso. los resultados de nuestros experimentos num\u00e9ricos demuestran que el algoritmo es capaz de localizar los tumores y reconstruir las distribuciones de los par\u00e1metros diel\u00e9ctricos dentro de la mama de una manera eficiente. El algoritmo no solo detecta el posible tumor y aproxima correctamente su tama\u00f1o, sino que adem\u00e1s es capaz de caracterizar el tejido sano por su contenido en fibra y grasa y aproximar las propiedades diel\u00e9ctricas del tumor, que pueden ser reflejo de su malignidad.<\/p>\n

 <\/p>\n

Datos acad\u00e9micos de la tesis doctoral \u00abMicrowave medical imaging using level set techniques<\/strong>\u00ab<\/h3>\n
    \n
  • T\u00edtulo de la tesis:<\/strong>\u00a0 Microwave medical imaging using level set techniques <\/li>\n
  • Autor:<\/strong>\u00a0 Natalia Irishina <\/li>\n
  • Universidad:<\/strong>\u00a0 Carlos III de Madrid<\/li>\n
  • Fecha de lectura de la tesis:<\/strong>\u00a0 13\/02\/2009<\/li>\n<\/ul>\n

     <\/p>\n

    Direcci\u00f3n y tribunal<\/h3>\n
      \n
    • Director de la tesis<\/strong>\n
        \n
      • Oliver Dorn<\/li>\n<\/ul>\n<\/li>\n
      • Tribunal<\/strong>\n
          \n
        • Presidente del tribunal: Luis L\u00f3pez bonilla <\/li>\n
        • Carlos Martel escobar (vocal)<\/li>\n
        • villie Kolehmainen (vocal)<\/li>\n
        • Jos\u00e9 Luis Rojo alvarez (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

           <\/p>\n","protected":false},"excerpt":{"rendered":"

          Tesis doctoral de Natalia Irishina El c\u00e1ncer de mama es una de las enfermedades que causan una mayor mortalidad entre […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[18550,13227],"tags":[30810,133019,30811,189874,134928,189875],"class_list":["post-91688","post","type-post","status-publish","format-standard","hentry","category-carlos-iii-de-madrid","category-simulacion","tag-carlos-martel-escobar","tag-jose-luis-rojo-alvarez","tag-luis-lopez-bonilla","tag-natalia-irishina","tag-oliver-dorn","tag-villie-kolehmainen"],"_links":{"self":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/91688","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/comments?post=91688"}],"version-history":[{"count":0,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/posts\/91688\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/media?parent=91688"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/categories?post=91688"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.deberes.net\/tesis\/wp-json\/wp\/v2\/tags?post=91688"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}