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Author (up) Fernando Vilariño; Petia Radeva edit  openurl
  Title Cardiac Segmentation with Discriminant Active Contours Type Book Chapter
  Year 2003 Publication Abbreviated Journal  
  Volume Issue Pages 211–217  
  Keywords  
  Abstract Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods.  
  Address Palma de Mallorca  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CCIA  
  Notes MV;MILAB;SIAI Approved no  
  Call Number BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 Serial 426  
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