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[02380] PDE methods for joint reconstruction-segmentation of images

  • Session Time & Room : 4E (Aug.24, 17:40-19:20) @A502
  • Type : Contributed Talk
  • Abstract : In practical image segmentation tasks, the image must first be reconstructed from indirect/damaged/noisy observations. Traditionally, reconstruction-segmentation would be performed in sequence: first reconstruct, then segment. Joint reconstruction-segmentation performs reconstruction and segmentation simultaneously, using each to guide the other. Past joint reconstruction-segmentation has employed relatively simple segmentation algorithms, e.g. Chan–Vese. This talk will describe how joint reconstruction-segmentation can be performed using Bhattacharyya-flow-based segmentation (Michailovich et al., 2007) and graph-PDE-based segmentation (Merkurjev et al., 2013).
  • Classification : 94A08, 35Q93, 35R02
  • Format : Talk at Waseda University
  • Author(s) :
    • Jeremy Michael Budd (California Institute of Technology )
    • Franca Hoffmann (California Institute of Technology )
    • Allen Tannenbaum (Stony Brook University)
    • Yves van Gennip (Technische Universiteit Delft)
    • Carola-Bibiane Schönlieb (University of Cambridge)
    • Jonas Latz (Heriot-Watt University)