Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalizing neural network

Ester Bonmati; Yipeng Hu; Nikhil Sindhwani; Hans Peter Dietz; Jan D’hooge; Dean Barratt; Jan Deprest; Tom Vercauteren

doi:10.1117/1.JMI.5.2.021206

Translator Disclaimer

10 January 2018 Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalizing neural network

Ester Bonmati, Yipeng Hu, Nikhil Sindhwani, Hans Peter Dietz, Jan D’hooge, Dean Barratt, Jan Deprest, Tom Vercauteren

Author Affiliations +

J. of Medical Imaging, 5(2), 021206 (2018). https://doi.org/10.1117/1.JMI.5.2.021206

Google Scholar citations

Check Google Scholar for citing papers

Citing works (18 citations)

1. Helena Williams, Laura Cattani, Tom Vercauteren et al., "ASMUS@MICCAI - Automatic Tomographic Ultrasound Imaging Sequence Extraction of the Anal Sphincter.", Simplifying Medical Ultrasound , pg. 35, (2021); doi:10.1007/978-3-030-87583-1_4 Lens.org
2. Helena Williams, Laura Cattani, Dominique Van Schoubroeck et al., "Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings.", Ultrasound in medicine & biology 47(12), pg. 3470, (2021); doi:10.1016/j.ultrasmedbio.2021.08.009 Lens.org
3. Helena Williams, João Pedrosa, Laura Cattani et al., "MICCAI (1) - Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces", Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 , pg. 315, (2021); doi:10.1007/978-3-030-87193-2_30 Lens.org
4. Ester Bonmati, Yipeng Hu, Alexander Grimwood et al., "Voice-assisted Image Labelling for Endoscopic Ultrasound Classification using Neural Networks.", arXiv: Computer Vision and Pattern Recognition , pg. , (2021); doi: Lens.org
5. Zeping Huang, Enze Qu, Yishuang Meng et al., "Deep learning-based pelvic levator hiatus segmentation from ultrasound images.", European journal of radiology open 9, pg. 100412, (2022); doi:10.1016/j.ejro.2022.100412 Lens.org
6. Francis Jesmar P. Montalbo, "Diagnosing gastrointestinal diseases from endoscopy images through a multi-fused CNN with auxiliary layers, alpha dropouts, and a fusion residual block", Biomedical Signal Processing and Control 76, pg. 103683, (2022); doi:10.1016/j.bspc.2022.103683 Lens.org
7. Kriti, Jitendra Virmani, Ravinder Agarwal, "A Review of Segmentation Algorithms Applied to B-Mode Breast Ultrasound Images: A Characterization Approach", Archives of Computational Methods in Engineering 28(4), pg. 2567, (2020); doi:10.1007/s11831-020-09469-3 Lens.org
8. Anique T. M. Grob, F. van den Noort, C. H. van der Vaart et al., "Deep learning enables automatic quantitative assessment of puborectalis muscle and urogenital hiatus in plane of minimal hiatal dimensions.", Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology 54(2), pg. 270, (2019); doi:10.1002/uog.20181 Lens.org
9. Fei Feng, James A. Ashton-Miller, John O.L. DeLancey et al., "Convolutional neural network-based pelvic floor structure segmentation using magnetic resonance imaging in pelvic organ prolapse.", Medical physics 47(9), pg. 4281, (2020); doi:10.1002/mp.14377 Lens.org
10. Nooshin Ghavami, Yipeng Hu, Eli Gibson et al., "Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration.", Medical image analysis 58, pg. 101558, (2019); doi:10.1016/j.media.2019.101558 Lens.org
11. Helena Williams, Laura Cattani, Mohammad Yaqub et al., "ASMUS/PIPPI@MICCAI - Automatic C-Plane Detection in Pelvic Floor Transperineal Volumetric Ultrasound", Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis , pg. 136, (2020); doi:10.1007/978-3-030-60334-2_14 Lens.org
12. Alexander Grimwood, Helen McNair, Yipeng Hu et al., "Assisted Probe Positioning for Ultrasound Guided Radiotherapy Using Image Sequence Classification", arXiv: Computer Vision and Pattern Recognition , pg. , (2020); doi: Lens.org
13. Frieda van den Noort, Beril Sirmacek, Cornelis H. Slump, "Recurrent U-net for automatic pelvic floor muscle segmentation on 3D ultrasound.", arXiv: Image and Video Processing , pg. , (2021); doi: Lens.org
14. Alexander Grimwood, Helen McNair, Yipeng Hu et al., "MICCAI (3) - Assisted Probe Positioning for Ultrasound Guided Radiotherapy Using Image Sequence Classification", Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 , pg. 544, (2020); doi:10.1007/978-3-030-59716-0_52 Lens.org
15. Chi Wen Lung, Peter Ardhianto, Jen-Yung Tsai et al., "A Review of the Challenges in Deep Learning for Skeletal and Smooth Muscle Ultrasound Images", Applied Sciences 11(9), pg. 4021, (2021); doi:10.3390/app11094021 Lens.org
16. Fausto Milletari, Johann Frei, Seyed-Ahmad Ahmadi, "TOMAAT: volumetric medical image analysis as a cloud service", arXiv: Computer Vision and Pattern Recognition , pg. , (2018); doi: Lens.org
17. Helena Williams, Laura Cattani, Wenqi Li et al., "3D Convolutional Neural Network for Segmentation of the Urethra in Volumetric Ultrasound of the Pelvic Floor", 2019 IEEE International Ultrasonics Symposium (IUS) , pg. , (2019); doi:10.1109/ultsym.2019.8925792 Lens.org
18. Ester Bonmati, Yipeng Hu, Nikhil Sindhwani et al., "Medical Imaging: Image-Guided Procedures - Technical note: automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalising neural network", Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling 10576, pg. 123, (2018); doi:10.1117/12.2322403 Lens.org