Automatic segmentation and measurements of gestational sac using static B-mode ultrasound images
Author:
Affiliation:
1. The Univ. of Buckingham (United Kingdom)
2. Imperial College (United Kingdom)
Publisher
SPIE
Reference22 articles.
1. Automatic Identification of Early Miscarriage Based on Multiple Features Extracted From Ultrasound Images,;Khazendar,2014
2. Defining safe criteria to diagnose miscarriage: prospective observational multicentre study
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4. Clinical implications of intra- and interobserver reproducibility of transvaginal sonographic measurement of gestational sac and crown-rump length at 6-9 weeks' gestation
5. Automatic Identification of Miscarriage Cases Supported by Decision Strength Using Ultrasound Images of the Gestational Sac,;Khazendar,2015
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1. Automatic fetal ultrasound image segmentation of first trimester for measuring biometric parameters based on deep learning;Multimedia Tools and Applications;2023-08-31
2. Rapid and automatic assessment of early gestational age using computer vision and biometric measurements based on ultrasound video;Quantitative Imaging in Medicine and Surgery;2022-04
3. An Accurate Segmentation Framework for Static Ultrasound Images of the Gestational Sac;Journal of Medical and Biological Engineering;2022-01-17
4. Multi-level Trainable Segmentation for Measuring Gestational and Yolk Sacs from Ultrasound Images;Communications in Computer and Information Science;2017
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