التفاصيل البيبلوغرافية
| العنوان: |
Statistical Characterisation of Fetal Anatomy in Simple Obstetric Ultrasound Video Sweeps. |
| المؤلفون: |
Gleed, Alexander D.1 (AUTHOR) alexander.gleed@eng.ox.ac.uk, Mishra, Divyanshu1 (AUTHOR), Self, Alice2 (AUTHOR), Thiruvengadam, Ramachandran3 (AUTHOR), Desiraju, Bapu Koundinya3 (AUTHOR), Bhatnagar, Shinjini3 (AUTHOR), Papageorghiou, Aris T.2 (AUTHOR), Noble, J. Alison1 (AUTHOR) |
| المصدر: |
Ultrasound in Medicine & Biology. Jul2024, Vol. 50 Issue 7, p985-993. 9p. |
| مصطلحات موضوعية: |
*FETAL anatomy, *FETAL presentation, *ULTRASONIC imaging, *VIDEOS, *MACHINE learning |
| مستخلص: |
We present a statistical characterisation of fetal anatomies in obstetric ultrasound video sweeps where the transducer follows a fixed trajectory on the maternal abdomen. Large-scale, frame-level manual annotations of fetal anatomies (head, spine, abdomen, pelvis, femur) were used to compute common frame-level anatomy detection patterns expected for breech, cephalic, and transverse fetal presentations, with respect to video sweep paths. The patterns, termed statistical heatmaps, quantify the expected anatomies seen in a simple obstetric ultrasound video sweep protocol. In this study, a total of 760 unique manual annotations from 365 unique pregnancies were used. We provide a qualitative interpretation of the heatmaps assessing the transducer sweep paths with respect to different fetal presentations and suggest ways in which the heatmaps can be applied in computational research (e.g. , as a machine learning prior). The heatmap parameters are freely available to other researchers (https://github.com/agleed/calopus_statistical_heatmapsTest). [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
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