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The segmentation effect of style transfer on fetal head ultrasound image: a study of multi-source data

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机构: [1]College of Information Science and Technology, Jinan University, Guangzhou 510632, China [2]Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou 510632, China [3]Obstetrics and Gynecology Center, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China
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关键词: Style transfer Fetal head segmentation Fourier domain adaptation Data enhancement Ultrasound image

摘要:
The generalization ability of the fetal head segmentation method is reduced due to the data obtained by different machines, settings, and operations. To keep the generalization ability, we proposed a Fourier domain adaptation (FDA) method based on amplitude and phase to achieve better multi-source ultrasound data segmentation performance. Given the source/target image, the Fourier domain information was first obtained using fast Fourier transform. Secondly, the target information was mapped to the source Fourier domain through the phase adjustment parameter α and the amplitude adjustment parameter β. Thirdly, the target image and the preprocessed source image obtained through the inverse discrete Fourier transform were used as the input of the segmentation network. Finally, the dice loss was computed to adjust α and β. In the existing transform methods, the proposed method achieved the best performance. The adaptive-FDA method provides a solution for the automatic preprocessing of multi-source data. Experimental results show that it quantitatively improves the segmentation results and model generalization performance.© 2023. International Federation for Medical and Biological Engineering.

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出版当年[2022]版:
大类 | 3 区 工程技术
小类 | 3 区 数学与计算生物学 4 区 工程:生物医学 4 区 医学:信息 4 区 计算机:跨学科应用
最新[2025]版:
大类 | 4 区 医学
小类 | 3 区 数学与计算生物学 4 区 计算机:跨学科应用 4 区 工程:生物医学 4 区 医学:信息
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出版当年[2021]版:
Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Q3 ENGINEERING, BIOMEDICAL Q3 MEDICAL INFORMATICS
最新[2023]版:
Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Q3 ENGINEERING, BIOMEDICAL Q3 MEDICAL INFORMATICS

影响因子: 最新[2023版] 最新五年平均 出版当年[2021版] 出版当年五年平均 出版前一年[2020版] 出版后一年[2022版]

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第一作者机构: [1]College of Information Science and Technology, Jinan University, Guangzhou 510632, China
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通讯机构: [1]College of Information Science and Technology, Jinan University, Guangzhou 510632, China [2]Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Information Technology, Jinan University, Guangzhou 510632, China
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