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FISICO: Fast Image SegmentatIon COrrection.

Waldo ValenzuelaStephen J FergusonDominika IgnasiakGaëlle DiserensLevin HäniRoland WiestPeter VermathenChris BoeschMauricio Reyes
Published in: PloS one (2016)
Experimental results show that full segmentation corrections could be performed within an average correction time of 5.5±3.3 minutes and an average of 56.5±33.1 user interactions, while maintaining the quality of the final segmentation result within an average Dice coefficient of 0.92±0.02 for both anatomies. In addition, for users with different levels of expertise, our method yields a correction time and number of interaction decrease from 38±19.2 minutes to 6.4±4.3 minutes, and 339±157.1 to 67.7±39.6 interactions, respectively.
Keyphrases
  • deep learning
  • convolutional neural network
  • machine learning
  • magnetic resonance imaging
  • magnetic resonance