Automatic segmentation of ultrasound images of gastrocnemius medialis with different echogenicity levels using convolutional neural networks.

Automatic segmentation of ultrasound images of gastrocnemius medialis with different echogenicity levels using convolutional neural networks. Marzola, F.; van Alfen, N.; Salvi, M.; Santi, B. D.; Doorduin, J.; and Meiburger, K. M. In EMBC, pages 2113-2116, 2020. IEEE.

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Paper bibtex

@inproceedings{conf/embc/MarzolaASSDM20,
  added-at = {2020-09-21T00:00:00.000+0200},
  author = {Marzola, Francesco and van Alfen, Nens and Salvi, Massimo and Santi, Bruno De and Doorduin, Jonne and Meiburger, Kristen M.},
  biburl = {https://www.bibsonomy.org/bibtex/2916a4de94fae7aced6ea4a695b0f873e/dblp},
  booktitle = {EMBC},
  crossref = {conf/embc/2020},
  ee = {https://doi.org/10.1109/EMBC44109.2020.9176343},
  interhash = {fc6c5ded8dc0af8654ab046ea3b373b4},
  intrahash = {916a4de94fae7aced6ea4a695b0f873e},
  isbn = {978-1-7281-1990-8},
  keywords = {dblp},
  pages = {2113-2116},
  publisher = {IEEE},
  timestamp = {2020-09-22T11:35:21.000+0200},
  title = {Automatic segmentation of ultrasound images of gastrocnemius medialis with different echogenicity levels using convolutional neural networks.},
  url = {http://dblp.uni-trier.de/db/conf/embc/embc2020.html#MarzolaASSDM20},
  year = 2020
}

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