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Combining position-based dynamics and gradient vector flow for 4D mitral valve segmentation in TEE sequences.

Lennart TautzLars WalczakJoachim GeorgiiAmer JazaerliKatharina VellguthIsaac WamalaSimon SündermannVolkmar FalkAnja Hennemuth
Published in: International journal of computer assisted radiology and surgery (2019)
Our approach enables to segment the mitral valve in 4D TEE image data with normal and pathological valve closing behavior. With this method, in addition to the quantification of the remaining orifice area, shape and dimensions of the coaptation zone can be analyzed and considered for planning and surgical result assessment.
Keyphrases
  • mitral valve
  • deep learning
  • left atrial
  • left ventricular
  • convolutional neural network
  • electronic health record
  • big data
  • artificial intelligence
  • machine learning
  • heart failure
  • aortic valve
  • genetic diversity