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A new calibration approach to graph-based semantic segmentation

Riva, Mateus

Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Matemática e Estatística 2018-12-13

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  • Título:
    A new calibration approach to graph-based semantic segmentation
  • Autor: Riva, Mateus
  • Orientador: Cesar Junior, Roberto Marcondes
  • Assuntos: Imageamento De Ressonância Magnética; Métodos Estruturais; Segmentação Baseada Em Grafos; Visão Computacional; Computer Vision; Graph-Based Segmentation; Magnetic Resonance Imaging; Structural Methods
  • Notas: Dissertação (Mestrado)
  • Descrição: We introduce a calibration method for semantic segmentation of images utilizing statistical-relational graphs (SRGs), with a particular focus on pediatric Magnetic Resonance Imaging (MRI). The SRG provides a representation of a structured scene, describing both the attributes of each object of interest and the nature of their relationships, such as relative position in space. Each vertex in the graph represents an object of interest and each edge represents the relationship between two objects. Semantic segmentation can thus be performed by matching an SRG built from an observed image to a previously-built model SRG. We develop a calibration method for assessing the quality of SRG segmentation given a set of parameters, as well as an exploration of several sets of parameters applied to MRI. We present the validity and usefulness of the calibration technique, along with preliminary results on real MRI data segmentation. We additionally discuss future work on improving real data SRG-based segmentation.
  • DOI: 10.11606/D.45.2019.tde-25092019-133337
  • Editor: Biblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Instituto de Matemática e Estatística
  • Data de criação/publicação: 2018-12-13
  • Formato: Adobe PDF
  • Idioma: Inglês

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