Conference item
Automated characteriazation of the fetal heart in ultrasound images using fully convolutional neural networks
- Abstract:
-
Automatic analysis of fetal echocardiography screening images could aid in the identification of congenital heart diseases. The first step towards automatic fetal echocardiography analysis is locating the fetal heart in an image and identifying the viewing (imaging) plane. This is highly challenging since the fetal heart is small with relatively indistinct anatomical structural appearance. This is further compounded by the presence of artefacts in ultrasound images. Herein we provide a state-...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Bibliographic Details
- Publisher:
- IEEE Publisher's website
- Host title:
- 2017 IEEE 14TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2017)
- Journal:
- Proceedings of the 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) Journal website
- Pages:
- 671-674
- Publication date:
- 2017-06-17
- Acceptance date:
- 2017-01-01
- Event title:
- 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)
- Event location:
- Melbourne, Australia
- Event website:
- https://biomedicalimaging.org/2017/
- Event start date:
- 2017-04-18
- Event end date:
- 2017-04-21
- DOI:
- EISSN:
-
1945-8452
- ISSN:
-
1945-7928
- ISBN:
- 9781509011711
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
709252
- Local pid:
- pubs:709252
- Deposit date:
- 2020-04-30
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2017
- Rights statement:
- © 2017 IEEE.
- Notes:
- This paper was presented at the 14th IEEE International Symposium on Biomedical Imaging, 18th - 21st April 2017, Melbourne, Australia. This is the accepted manuscript version of the article. The final version is available from IEEE at: https://doi.org/10.1109/ISBI.2017.7950609
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