Super resolution methods for depth estimation in light sheet light field microscopy

In this Master's Thesis we explore enhanced depth estimation in light fields acquired with microscopes. We propose a neural network architecture for the production of novel angular views. We evaluate the performance of our method by comparing the precision of depth estimation in the HCI Light F...

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Autores:
Madrid Wolff, Jorge Andrés
Tipo de recurso:
Fecha de publicación:
2019
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/44325
Acceso en línea:
http://hdl.handle.net/1992/44325
Palabra clave:
Microscopia - Técnica - Investigaciones
Microscopia fluorescente - Investigaciones
Redes neurales (Computadores) - Aplicaciones - Investigaciones
Ingeniería
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/4.0/
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spelling Al consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Arbeláez Escalante, Pablo Andrés7b73426f-f63b-413f-b44b-ddfa70416b65400Forero Shelton, Antonio Manuvirtual::1856-1Madrid Wolff, Jorge Andrés39340500Valderrama Manrique, Mario AndrésOlarte, Omar2020-09-03T14:37:15Z2020-09-03T14:37:15Z2019http://hdl.handle.net/1992/44325u827129.pdfinstname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/In this Master's Thesis we explore enhanced depth estimation in light fields acquired with microscopes. We propose a neural network architecture for the production of novel angular views. We evaluate the performance of our method by comparing the precision of depth estimation in the HCI Light Field Benchmark of its state of the art algorithm when receiving regular vs. upsampled light fields. We demonstrate reductions in the error of depth estimation by up to 12-35 percentage points. Complementarily, we present an approach to increase angular resolution in light field microscopy by providing optical sectioning of the sample with light sheets from a digital micromirror device. We also present a Fourier optics model of pattern projection from the DMD to the sample by a tube lens and a microscope objective.En esta tesis de maestría exploramos la estimación mejorada de profundidad en campos de luz adquiridos con microscopios. Proponemos una arquitectura de red neuronal para la predicción de nuevas vistas angulares. Evaluamos el desempeño de nuestro método comparando la precisión en la estimación de profundidad del algoritmo del estado del arte del HCI Light Field Benchmark al suministrarle campos de luz normales versus campos de luz a los que se les ha hecho upsampling angular. Demostramos reducciones en el error de la estimación de profundidad de hasta 12 a 35 puntos percentuales. Complementariamente, presentamos un método para incrementar la resolución en microscopía de campo de luz al hacer seccionamiento óptico de la muestra mediante hojas de luz producidas por un arreglo de microespejos (DMD). Además, presentamos un modelo de óptica de Fourier para la proyección de patrones del DMD a la muestra.Magíster en Ingeniería BiomédicaMaestría10 hojasapplication/pdfengUniandesMaestría en Ingeniería BiomédicaFacultad de IngenieríaDepartamento de Ingeniería Biomédicainstname:Universidad de los Andesreponame:Repositorio Institucional SénecaSuper resolution methods for depth estimation in light sheet light field microscopyTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesishttp://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/TMMicroscopia - Técnica - InvestigacionesMicroscopia fluorescente - InvestigacionesRedes neurales (Computadores) - Aplicaciones - InvestigacionesIngenieríaPublicationhttps://scholar.google.es/citations?user=0_jvORsAAAAJvirtual::1856-1https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001289730virtual::1856-1d8390b22-58d0-4d8c-9abb-d88e0327611dvirtual::1856-1d8390b22-58d0-4d8c-9abb-d88e0327611dvirtual::1856-1ORIGINALu827129.pdfapplication/pdf14790759https://repositorio.uniandes.edu.co/bitstreams/c7433078-ab5c-4d96-9e90-4455e998b54b/download81637fd1e7e3d0ec3d658eb6946bb519MD51TEXTu827129.pdf.txtu827129.pdf.txtExtracted texttext/plain49218https://repositorio.uniandes.edu.co/bitstreams/c6c1bedf-e41f-4bd6-8c57-bccb9aa2e751/downloadb233630ac70fa5236b1cedec6794a20dMD54THUMBNAILu827129.pdf.jpgu827129.pdf.jpgIM Thumbnailimage/jpeg8533https://repositorio.uniandes.edu.co/bitstreams/368b3fd5-17d2-40b5-8d77-082d7468cd3f/downloadafedfbbd081f97b2578438595396fdc7MD551992/44325oai:repositorio.uniandes.edu.co:1992/443252024-03-13 12:03:56.423http://creativecommons.org/licenses/by-nc-nd/4.0/open.accesshttps://repositorio.uniandes.edu.coRepositorio institucional Sénecaadminrepositorio@uniandes.edu.co
dc.title.es_CO.fl_str_mv Super resolution methods for depth estimation in light sheet light field microscopy
title Super resolution methods for depth estimation in light sheet light field microscopy
spellingShingle Super resolution methods for depth estimation in light sheet light field microscopy
Microscopia - Técnica - Investigaciones
Microscopia fluorescente - Investigaciones
Redes neurales (Computadores) - Aplicaciones - Investigaciones
Ingeniería
title_short Super resolution methods for depth estimation in light sheet light field microscopy
title_full Super resolution methods for depth estimation in light sheet light field microscopy
title_fullStr Super resolution methods for depth estimation in light sheet light field microscopy
title_full_unstemmed Super resolution methods for depth estimation in light sheet light field microscopy
title_sort Super resolution methods for depth estimation in light sheet light field microscopy
dc.creator.fl_str_mv Madrid Wolff, Jorge Andrés
dc.contributor.advisor.none.fl_str_mv Arbeláez Escalante, Pablo Andrés
Forero Shelton, Antonio Manu
dc.contributor.author.none.fl_str_mv Madrid Wolff, Jorge Andrés
dc.contributor.jury.none.fl_str_mv Valderrama Manrique, Mario Andrés
Olarte, Omar
dc.subject.armarc.es_CO.fl_str_mv Microscopia - Técnica - Investigaciones
Microscopia fluorescente - Investigaciones
Redes neurales (Computadores) - Aplicaciones - Investigaciones
topic Microscopia - Técnica - Investigaciones
Microscopia fluorescente - Investigaciones
Redes neurales (Computadores) - Aplicaciones - Investigaciones
Ingeniería
dc.subject.themes.none.fl_str_mv Ingeniería
description In this Master's Thesis we explore enhanced depth estimation in light fields acquired with microscopes. We propose a neural network architecture for the production of novel angular views. We evaluate the performance of our method by comparing the precision of depth estimation in the HCI Light Field Benchmark of its state of the art algorithm when receiving regular vs. upsampled light fields. We demonstrate reductions in the error of depth estimation by up to 12-35 percentage points. Complementarily, we present an approach to increase angular resolution in light field microscopy by providing optical sectioning of the sample with light sheets from a digital micromirror device. We also present a Fourier optics model of pattern projection from the DMD to the sample by a tube lens and a microscope objective.
publishDate 2019
dc.date.issued.es_CO.fl_str_mv 2019
dc.date.accessioned.none.fl_str_mv 2020-09-03T14:37:15Z
dc.date.available.none.fl_str_mv 2020-09-03T14:37:15Z
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
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dc.identifier.pdf.none.fl_str_mv u827129.pdf
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dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional Séneca
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identifier_str_mv u827129.pdf
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dc.format.extent.es_CO.fl_str_mv 10 hojas
dc.format.mimetype.es_CO.fl_str_mv application/pdf
dc.publisher.es_CO.fl_str_mv Uniandes
dc.publisher.program.es_CO.fl_str_mv Maestría en Ingeniería Biomédica
dc.publisher.faculty.es_CO.fl_str_mv Facultad de Ingeniería
dc.publisher.department.es_CO.fl_str_mv Departamento de Ingeniería Biomédica
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reponame:Repositorio Institucional Séneca
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