Sharma, H; Droste, R; Chatelain, P; Drukker, L; Papageorghiou, AT; Noble, JA; IEEE
(2019)
Spatio-Temporal Partitioning And Description Of Full-Length Routine Fetal Anomaly Ultrasound Scans.
In: 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), April 8th-11th 2019, Hilton Molino Stucky, Venice, Italy.
SGUL Authors: Papageorghiou, Aris
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Abstract
This paper considers automatic clinical workflow description of full-length routine fetal anomaly ultrasound scans using deep learning approaches for spatio-temporal video analysis. Multiple architectures consisting of 2D and 2D + t CNN, LSTM, and convolutional LSTM are investigated and compared. The contributions of short-term and long-term temporal changes are studied, and a multi-stream framework analysis is found to achieve the best top-l accuracy =0.77 and top-3 accuracy =0.94. Automated partitioning and characterisation on unlabelled full-length video scans show high correlation (ρ=0.95, p=0.0004) with workflow statistics of manually labelled videos, suggesting practicality of proposed methods.
| Item Type: | Conference or Workshop Item (Paper) | |||||||||
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| Additional Information: | © © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||
| Keywords: | Fetal anomaly scan, spatio-temporal analysis, video classification, ultrasound, clinical workflow | |||||||||
| SGUL Research Institute / Research Centre: | Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) > Centre for Clinical Education (INMECE ) |
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| Journal or Publication Title: | 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019) | |||||||||
| ISSN: | 1945-7928 | |||||||||
| Publisher License: | Publisher's own licence | |||||||||
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| Web of Science ID: | WOS:000485040000208 | |||||||||
| URI: | https://openaccess.sgul.ac.uk/id/eprint/111367 |
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