@inproceedings{DBLP:conf/miccai/MengBSHRGHTZTMR18,
  author    = {Qingjie Meng and
               Christian F. Baumgartner and
               Matthew Sinclair and
               James Housden and
               Martin Rajchl and
               Alberto G{\'{o}}mez and
               Benjamin Hou and
               Nicolas Toussaint and
               Veronika A. M. Zimmer and
               Jeremy Tan and
               Jacqueline Matthew and
               Daniel Rueckert and
               Julia A. Schnabel and
               Bernhard Kainz},
  title     = {Automatic Shadow Detection in 2D Ultrasound Images},
  booktitle = {DATRA/PIPPI@MICCAI},
  series    = {Lecture Notes in Computer Science},
  volume    = {11076},
  pages     = {66--75},
  publisher = {Springer},
  year      = {2018},
  doi = {10.1007/978-3-030-00807-9\_7},
  url = {https://doi.org/10.1007/978-3-030-00807-9\_7},
  abstract = {Automatically detecting acoustic shadows is important for ultrasound analysis tasks ranging from segmentation to landmark detection. This work generates a pixel-wise, shadow-focused confidence map from weakly labelled, anatomically focused images by initializing potential shadow regions with a classification task, extending them with a generative adversarial model and incorporating intensity information through a distance matrix. The method highlights shadow regions in fetal-screening ultrasound and improves on prior methods and downstream biometric measurements.},
}