---
res:
  bibo_abstract:
  - In cortex surface segmentation, the extracted surface is required to have a particular
    topology, namely, a two-sphere. We present a new method for removing topology
    noise of a curve or surface within the level set framework, and thus produce a
    cortical surface with correct topology. We define a new energy term which quantifies
    topology noise. We then show how to minimize this term by computing its functional
    derivative with respect to the level set function. This method differs from existing
    methods in that it is inherently continuous and not digital; and in the way that
    our energy directly relates to the topology of the underlying curve or surface,
    versus existing knot-based measures which are related in a more indirect fashion.
    The proposed flow is validated empirically.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Chao
      foaf_name: Chen, Chao
      foaf_surname: Chen
      foaf_workInfoHomepage: http://www.librecat.org/personId=3E92416E-F248-11E8-B48F-1D18A9856A87
  - foaf_Person:
      foaf_givenName: Daniel
      foaf_name: Freedman, Daniel
      foaf_surname: Freedman
  bibo_doi: 10.1007/978-3-642-18421-5_4
  bibo_volume: 6533
  dct_date: 2010^xs_gYear
  dct_language: eng
  dct_publisher: Springer@
  dct_title: Topology noise removal for curve  and surface evolution@
...