{"id":12081,"date":"2023-07-25T10:35:01","date_gmt":"2023-07-25T10:35:01","guid":{"rendered":"https:\/\/projectsofar.info\/aisuperior\/?post_type=news&p=12081"},"modified":"2023-09-28T10:53:59","modified_gmt":"2023-09-28T10:53:59","slug":"ai-superior-boehringer-ingelheim-publish-a-joint-survey-paper-for-midl-2023","status":"publish","type":"news","link":"https:\/\/aisuperior.com\/es\/news\/ai-superior-boehringer-ingelheim-publish-a-joint-survey-paper-for-midl-2023\/","title":{"rendered":"AI Superior y Boehringer Ingelheim publican un estudio conjunto para MIDL 2023"},"content":{"rendered":"

Estamos orgullosos de anunciar nuestra reciente colaboraci\u00f3n con\u00a0Boehringer Ingelheim<\/a>\u00a0en un art\u00edculo de encuesta titulado \u201cUna evaluaci\u00f3n comparativa de m\u00e9todos de traducci\u00f3n de imagen a imagen para la transferencia de tinciones en histopatolog\u00eda\u201d, que ha sido aceptado en la prestigiosa conferencia Medical Imaging with Deep Learning (MIDL 2023).<\/p>\n

Nuestro estudio eval\u00faa minuciosamente doce enfoques de transferencia de tinciones, que constan de tres m\u00e9todos de procesamiento de im\u00e1genes tradicionales y nueve basados en GAN. Bas\u00e1ndose en medidas cuantitativas complementarias y evaluaciones visuales realizadas por pat\u00f3logos, la investigaci\u00f3n compara las fortalezas y debilidades de cada enfoque de transferencia de tinciones, proporcionando informaci\u00f3n valiosa para avanzar en la histopatolog\u00eda y capacitar a los investigadores y profesionales m\u00e9dicos para tomar decisiones informadas.<\/p>\n

Este esfuerzo de colaboraci\u00f3n marca un hito importante en la aplicaci\u00f3n de la IA y el aprendizaje profundo en histopatolog\u00eda y allana el camino para futuros avances en diagn\u00f3stico e im\u00e1genes m\u00e9dicas.<\/p>\n

El documento de la encuesta ya est\u00e1 disponible para descargar.\u00a0aqu\u00ed<\/a>\u00a0y, en l\u00ednea con nuestro compromiso de fomentar la colaboraci\u00f3n y el progreso, estamos encantados de publicar el c\u00f3digo para el marco de evaluaci\u00f3n comparativa bajo una licencia de c\u00f3digo abierto.<\/p>","protected":false},"author":2,"featured_media":12082,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","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":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","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-opacity":"","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-opacity":"","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-opacity":"","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-opacity":"","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-opacity":"","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-opacity":"","overlay-gradient":""}}},"news_categories":[],"class_list":["post-12081","news","type-news","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"\nAI Superior & Boehringer Ingelheim Publish a Joint Survey Paper for MIDL 2023 - aisuperior<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/aisuperior.com\/es\/news\/ai-superior-boehringer-ingelheim-publish-a-joint-survey-paper-for-midl-2023\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI Superior & Boehringer Ingelheim Publish a Joint Survey Paper for MIDL 2023 - aisuperior\" \/>\n<meta property=\"og:description\" content=\"We are proud to announce our recent collaboration with\u00a0Boehringer Ingelheim\u00a0on a survey paper titled \u201cA comparative evaluation of image-to-image translation methods for stain transfer in histopathology\u201d, that has been accepted at the prestigious Medical Imaging with Deep Learning (MIDL 2023) conference. 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