DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks

  title={DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks},
  author={Martin Rajchl and M. J. Lee and O. Oktay and K. Kamnitsas and J. Passerat-Palmbach and Wenjia Bai and Bernhard Kainz and D. Rueckert},
  journal={IEEE Transactions on Medical Imaging},
  • Martin Rajchl, M. J. Lee, +5 authors D. Rueckert
  • Published 2017
  • Computer Science, Medicine
  • IEEE Transactions on Medical Imaging
  • In this paper, we propose <italic>DeepCut</italic>, a method to obtain pixelwise object segmentations given an image dataset labelled weak annotations, in our case bounding boxes. [...] Key Method It extends the approach of the well-known <italic>GrabCut</italic> <xref ref-type="bibr" rid="ref1">[1]</xref> method to include machine learning by training a neural network classifier from bounding box annotations.Expand Abstract
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