In vivo classification of inflammation in blood vessels with convolutional neural networks

Stuart McIlroy, Yoshimasa Kubo, Thomas Trappenberg, James Toguri, Christian Lehmann

Résultat de recherche: Conference contribution

4 Citations (Scopus)

Résumé

An emerging field in medical diagnostics is the study of micro-circulations in blood vessels. Several characteristics of the micro-circulations in blood vessels have been shown to predict inflammation in a patient's tissue. The characteristics are video recorded via a camera inserted into the subject. At present, the analysis of the videos are done manually by visual inspection to determine inflammation. In our paper, we propose a technique to automatically classify the videos as containing inflammation or not. Our technique uses a convolutional neural network which classifies many different segments of images from a video and averages the predictions. Our network achieves an accuracy of 83%. We further divide inflammation into extreme and moderate inflammation and our network achieves an accuracy of 80%. This is the first step in developing methods that can perform a better quantitative analysis of inflammation to speed up medical diagnosis.

Langue d'origineEnglish
Titre de la publication principale2017 International Joint Conference on Neural Networks, IJCNN 2017 - Proceedings
Maison d'éditionInstitute of Electrical and Electronics Engineers Inc.
Pages3022-3027
Nombre de pages6
ISBN (électronique)9781509061815
DOI
Statut de publicationPublished - juin 30 2017
Événement2017 International Joint Conference on Neural Networks, IJCNN 2017 - Anchorage, United States
Durée: mai 14 2017mai 19 2017

Séries de publication

PrénomProceedings of the International Joint Conference on Neural Networks
Volume2017-May

Conference

Conference2017 International Joint Conference on Neural Networks, IJCNN 2017
Pays/TerritoireUnited States
VilleAnchorage
Période5/14/175/19/17

Note bibliographique

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus Subject Areas

  • Software
  • Artificial Intelligence

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