Artificial intelligence models derived from 2D transperineal ultrasound images in the clinical diagnosis of stress urinary incontinence

Zhang, Man; Lin, Xin; Zheng, Zhuo; Chen, Ying; Ren, Yong; Zhang, Xinling

doi:10.1007/s00192-021-04859-y

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…The mid-sagittal plane of the pelvic floor is mainly used to diagnose organ prolapse and its severity, pressure urinary incontinence and its severity, pelvic floor lesions, which are important parts of female pelvic floor assessment [2][3][4]. In 2021, Zhang [25] . The results showed that the AUC of Model D (0.922) was significantly higher than that of the other three models (0.771, 0.862, and 0.827, as shown in Fig.…”

Section: Automatic Identification and Diagnosis Of The Midsagittal Pl...mentioning

confidence: 99%

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

Qu¹,

Zhang²

2023

Advanced Ultrasound in Diagnosis and Therapy

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Artificial intelligence-based pelvic floor ultrasound helps the diagnosis, preoperative assessment, and postoperative monitoring of female pelvic floor dysfunction (FPFD). The application of artificial intelligence in pelvic floor ultrasound mainly includes automatic segmentation and measurement, the diagnosis of muscle injury, childbirth prediction and postoperational evaluation. It can not only overcome the problem of operator experience dependence but also improve work efficiency and simplify the workflow, which has popularized the application of pelvic floor ultrasound. However, most of the current research is still limited to the automatic segmentation of three-dimensional axial plane levator hiatus (LH). The automatic reconstruction, real-time tracking of 3D/4D images and the imaging navigation of pelvic floor surgery remain major challenges for researchers.

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Section: Automatic Identification and Diagnosis Of The Midsagittal Pl...mentioning

confidence: 99%

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

Qu¹,

Zhang²

2023

Advanced Ultrasound in Diagnosis and Therapy

View full text Add to dashboard Cite

show abstract

Ultrasound assessment of bladder descent and its correlation with prolapse severity in Chinese women: a prospective multicenter study

Wang

Zheng

et al. 2022

Int Urogynecol J

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Validation of a built-in software in automatically reconstructing the tomographic images of the levator ani muscle

Qu,

Wu,

Zhang

et al. 2023

Int Urogynecol J

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Artificial intelligence models derived from 2D transperineal ultrasound images in the clinical diagnosis of stress urinary incontinence

Cited by 4 publications

References 17 publications

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

Advanced Application of Artificial Intelligence for Pelvic Floor Ultrasound in Diagnosis and Treatment

Ultrasound assessment of bladder descent and its correlation with prolapse severity in Chinese women: a prospective multicenter study

Validation of a built-in software in automatically reconstructing the tomographic images of the levator ani muscle

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