Automatic Segmentation of the Left Ventricle in 3D SPECT Data by Registration with a Dynamic Anatomic Model

@article{Dornheim2005AutomaticSO,
  title={Automatic Segmentation of the Left Ventricle in 3D SPECT Data by Registration with a Dynamic Anatomic Model},
  author={Lars Dornheim and Klaus D. T{\"o}nnies and Kat Dixon},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2005},
  volume={8 Pt 1},
  pages={335-42}
}
We present a fully automatic 3D segmentation method for the left ventricle (LV) in human myocardial perfusion SPECT data. This model-based approach consists of 3 phases: 1. finding the LV in the dataset, 2. extracting its approximate shape and 3. segmenting its exact contour. Finding of the LV is done by flexible pattern matching, whereas segmentation is achieved by registering an anatomical model to the functional data. This model is a new kind of stable 3D mass spring model using direction… CONTINUE READING