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- W4377700870 abstract "Deep learning Techniques are rapidly becoming the industry level for analyzing fetal ultrasound pictures. Despite the significant number of survey studies that have previously been published on this subject, the majority focus on image analysis-related Medical Science or do not include all fetal Ultrasound deep learning applications. We have collected 30 research papers released after 2016; this study examines the most recent work on the subject. Each study is evaluated and commented on from both a technique and an application standpoint. The studies were considered for the analysis of anatomical fetus structure. The primary limits and open concerns for each category are mentioned. Summary tables are supplied to make it easier to compare the various techniques. Also presented are publicly accessible data sets and key performance metrics indicators widely used to evaluate algorithmic Behaviour regarding deep learning techniques used. Here studies wrap up with a condemning overview of the present date in Deep learning algorithms for fetal Ultrasound image processing and a conclusion of nowadays problems that researchers working in the field must address to transform research techniques into practical clinical practice." @default.
- W4377700870 created "2023-05-24" @default.
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- W4377700870 date "2023-04-07" @default.
- W4377700870 modified "2023-10-17" @default.
- W4377700870 title "Review on Ultrasound-Image Analysis of Fetus Using Deep Learning" @default.
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- W4377700870 doi "https://doi.org/10.1109/i2ct57861.2023.10126500" @default.
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