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Assessing knee OA severity with CNN attention-based end-to-end architectures

Author
Górriz, M.; Antony, J.; McGuinness, K.; Giro, X.; O'Connor, N.
Type of activity
Presentation of work at congresses
Name of edition
2nd International conference on Medical Imaging with Deep Learning
Date of publication
2019
Presentation's date
2019-07-09
Book of congress proceedings
International Conference on Medical Imaging with Deep Learning: 8-10 July 2019, London, United Kingdom: proceedings of Machine Learning Research
First page
197
Last page
214
Project funding
Multimodal Signal Processing and Machine Learning on Graphs
Repository
http://hdl.handle.net/2117/166395 Open in new window
https://openreview.net/forum?id=B1epyN8rlV Open in new window
URL
http://proceedings.mlr.press/v102/gorriz19a.html Open in new window
Abstract
This work proposes a novel end-to-end convolutional neural network (CNN) architecture to automatically quantify the severity of knee osteoarthritis (OA) using X-Ray images, which incorporates trainable attention modules acting as unsupervised fine-grained detectors of the region of interest (ROI). The proposed attention modules can be applied at different levels and scales across any CNN pipeline helping the network to learn relevant attention patterns over the most informative parts of the imag...
Citation
Górriz, M. [et al.]. Assessing knee OA severity with CNN attention-based end-to-end architectures. A: International conference on Medical Imaging with Deep Learning. "International Conference on Medical Imaging with Deep Learning: 8-10 July 2019, London, United Kingdom: proceedings of Machine Learning Research". 2019, p. 197-214.
Keywords
Computer vision, Conbolutional neural networks, Deep learning, Knee osteoarthritis, Medical imaging
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Górriz, Marc  (author and speaker )
  • Antony, Joseph  (author and speaker )
  • McGuinness, Kevin  (author and speaker )
  • Giro Nieto, Xavier  (author and speaker )
  • O'Connor, Noel  (author and speaker )

Attachments