Results 51 to 60 of about 222,683 (279)

Recurrent U-net for automatic pelvic floor muscle segmentation on 3D ultrasound [PDF]

arXiv, 2021
The prevalance of pelvic floor problems is high within the female population. Transperineal ultrasound (TPUS) is the main imaging modality used to investigate these problems. Automating the analysis of TPUS data will help in growing our understanding of pelvic floor related problems.
arxiv  

Effects of Pelvic-Floor Muscle Training in Patients with Pelvic Organ Prolapse Approached with Surgery vs. Conservative Treatment: A Systematic Review

Journal of Personalized Medicine, 2022
The aim of this systematic review was to explore the effectiveness of pelvic-floor muscle training (PFMT) in the treatment of women with pelvic organ prolapse (POP) who had undergone either surgery or only conservative treatment, based on a selection of ...
Andrea Espiño-Albela, Carla Castaño-García, E. Díaz-Mohedo, A. Ibáñez-Vera   +3 more
semanticscholar   +1 more source

Pelvic floor MRI segmentation based on semi-supervised deep learning [PDF]

arXiv, 2023
The semantic segmentation of pelvic organs via MRI has important clinical significance. Recently, deep learning-enabled semantic segmentation has facilitated the three-dimensional geometric reconstruction of pelvic floor organs, providing clinicians with accurate and intuitive diagnostic results.
arxiv  

Three-dimensional reconstruction and characterization of bladder deformations [PDF]

arXiv, 2023
Background and Objective: Pelvic floor disorders are prevalent diseases and patient care remains difficult as the dynamics of the pelvic floor remains poorly known. So far, only 2D dynamic observations of straining exercises at excretion are available in the clinics and the understanding of three-dimensional pelvic organs mechanical defects is not yet ...
arxiv  

Effect of Pelvic Floor Muscle Training Using Pressure Biofeedback on Pelvic Floor Muscle Contraction and Trunk Muscle Activity in Sitting in Healthy Women

Healthcare, 2022
Pelvic floor muscle training (PFMT) has been recommended as the first choice as one of the effective methods for preventing and improving urinary incontinence (UI).
Min-joo Ko, Min-Suk Koo, Eun-joo Jung, Won-jeong Jeong, Jae-seop Oh   +4 more
semanticscholar   +1 more source

Pelvic floor rehabilitation in the treatment of mixed urinary incontinence among women

Egyptian Rheumatology and Rehabilitation, 2021
Background Mixed urinary incontinence (MUI) is a common underreported problem among females; it has a major effect on patients’ quality of life. Treatment may be difficult since a single modality cannot be enough to alleviate both the urge and the stress
Nehad Mohamed Elshatby, Mohamed Hassan Imam, Mohamed Shafik Shoukry, Marwa Mohamed Hassan, Emmanuel Kamal Aziz Saba   +4 more
doaj   +1 more source

Fully Automated Organ Segmentation in Male Pelvic CT Images [PDF]

Balagopal A, Kazemifar S, Nguyen D, Lin M H, Hannan R, Owrangi A and Jiang S 2018 Fully automated organ segmentation in male pelvic CT images Phys. Med. Biol. 63 245015, 2018
Accurate segmentation of prostate and surrounding organs at risk is important for prostate cancer radiotherapy treatment planning. We present a fully automated workflow for male pelvic CT image segmentation using deep learning. The architecture consists of a 2D localization network followed by a 3D segmentation network for volumetric segmentation of ...
arxiv   +1 more source

Effectiveness of pelvic floor muscle training with and without electromyographic biofeedback for urinary incontinence in women: multicentre randomised controlled trial

British medical journal, 2020
Objective To assess the effectiveness of pelvic floor muscle training (PFMT) plus electromyographic biofeedback or PFMT alone for stress or mixed urinary incontinence in women. Design Parallel group randomised controlled trial.
S. Hagen, A. Elders, Susan Stratton, N. Sergenson, C. Bugge, S. Dean, J. Hay-Smith, M. Kilonzo, M. Dimitrova, M. Abdel-Fattah, W. Agur, J. Booth, C. Glazener, K. Guerrero, A. McDonald, J. Norrie, Louise R. Williams, D. McClurg   +17 more
semanticscholar   +1 more source

Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalising neural network [PDF]

, 2017
Segmentation of the levator hiatus in ultrasound allows to extract biometrics which are of importance for pelvic floor disorder assessment. In this work, we present a fully automatic method using a convolutional neural network (CNN) to outline the levator hiatus in a 2D image extracted from a 3D ultrasound volume.
arxiv   +1 more source

OnUVS: Online Feature Decoupling Framework for High-Fidelity Ultrasound Video Synthesis [PDF]

arXiv, 2023
Ultrasound (US) imaging is indispensable in clinical practice. To diagnose certain diseases, sonographers must observe corresponding dynamic anatomic structures to gather comprehensive information. However, the limited availability of specific US video cases causes teaching difficulties in identifying corresponding diseases, which potentially impacts ...
arxiv