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- Title
EP34.29: Deep attention networks for the prediction of pouch of Douglas obliteration from transvaginal ultrasound sliding sign videos.
- Authors
O'Shea, K.; Leonardi, M.; Bolton, R.A.; Condous, G.; Lu, C.
- Abstract
The data set used for model development consists of 88 ultrasound recordings from different sonographic machines to determine POD obliteration of women presenting with chronic pelvic pain, using the dynamic real-time "sliding sign" technique. In spite of the limited dataset, we have demonstrated the potential of using deep attention-based neural networks for the preoperative prediction of POD obliteration from a number of "sliding-sign" studies.
- Subjects
VIDEOS; TRANSVAGINAL ultrasonography; OBSTETRICS; PELVIC pain; IMAGE recognition (Computer vision)
- Publication
Ultrasound in Obstetrics & Gynecology, 2019, Vol 54, p448
- ISSN
0960-7692
- Publication type
Article
- DOI
10.1002/uog.21819