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Tool for 3D analysis and segmentation of retinal layers in volumetric SD-OCT images

datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapt_PT
dc.contributor.advisorMora, André
dc.contributor.authorAscenso, João Paulo Isidoro
dc.date.accessioned2017-01-26T14:12:14Z
dc.date.available2017-01-26T14:12:14Z
dc.date.issued2016-09
dc.date.submitted2017-01
dc.description.abstractWith the development of optical coherence tomography in the spectral domain (SD-OCT), it is now possible to quickly acquire large volumes of images. Typically analyzed by a specialist, the processing of the images is quite slow, consisting on the manual marking of features of interest in the retina, including the determination of the position and thickness of its different layers. This process is not consistent, the results are dependent on the clinician perception and do not take advantage of the technology, since the volumetric information that it currently provides is ignored. Therefore is of medical and technological interest to make a three-dimensional and automatic processing of images resulting from OCT technology. Only then we will be able to collect all the information that these images can give us and thus improve the diagnosis and early detection of eye pathologies. In addition to the 3D analysis, it is also important to develop visualization tools for the 3D data. This thesis proposes to apply 3D graphical processing methods to SD-OCT retinal images, in order to segment retinal layers. Also, to analyze the 3D retinal images and the segmentation results, a visualization interface that allows displaying images in 3D and from different perspectives is proposed. The work was based on the use of the Medical Imaging Interaction Toolkit (MITK), which includes other open-source toolkits. For this study a public database of SD-OCT retinal images will be used, containing about 360 volumetric images of healthy and pathological subjects. The software prototype allows the user to interact with the images, apply 3D filters for segmentation and noise reduction and render the volume. The detection of three surfaces of the retina is achieved through intensity-based edge detection methods with a mean error in the overall retina thickness of 3.72 0.3 pixels.pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/19918
dc.language.isoengpt_PT
dc.subjectRetinal SD-OCTpt_PT
dc.subjectRetinal layerspt_PT
dc.subject3D automatic segmentationpt_PT
dc.subject3D visualizationpt_PT
dc.subjectMITKpt_PT
dc.titleTool for 3D analysis and segmentation of retinal layers in volumetric SD-OCT imagespt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Engenharia Electrotécnica e de Computadorespt_PT

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