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Automatic detection of kidney in 3D pediatric ultrasound images using deep neural networks.

, , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10575 of SPIE Proceedings, page 105751Z. SPIE, (2018)

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Three-Dimensional Multi-Frequency Shear Wave Absolute Vibro-Elastography (3D S-WAVE) With a Matrix Array Transducer: Implementation and Preliminary In Vivo Study of the Liver., , , , , , , , , and 2 other author(s). IEEE Trans. Medical Imaging, 40 (2): 648-660 (2021)Ultrasonic fatty liver imaging., , and . EUSIPCO, page 2591-2595. IEEE, (2015)Positive Delta Detection for Alpha Shape Segmentation of 3D Ultrasound Images of Pathologic Kidneys., , , , and . MICCAI (3), volume 9351 of Lecture Notes in Computer Science, page 711-718. Springer, (2015)Quantification of kidneys from 3D ultrasound in pediatric hydronephrosis., , , , , , and . EMBC, page 157-160. IEEE, (2015)Pediatric Hydronephrosis Severity Assessment Using Convolutional Neural Networks With Standardized Ultrasound Images., , , , , , , , and . ISBI, page 1803-1806. IEEE, (2021)Segmentation of kidney in 3D-ultrasound images using Gabor-based appearance models., , , , , and . ISBI, page 633-636. IEEE, (2014)Standardized Analysis of Kidney Ultrasound Images for the Prediction of Pediatric Hydronephrosis Severity., , , , , , , , and . MLMI@MICCAI, volume 12966 of Lecture Notes in Computer Science, page 366-375. Springer, (2021)Graph-based surface extraction of the liver using locally adaptive priors for multimodal interventional image registration., , , , , and . Medical Imaging: Image-Guided Procedures, volume 8316 of SPIE Proceedings, page 83161O. SPIE, (2012)Renal Segmentation From 3D Ultrasound via Fuzzy Appearance Models and Patient-Specific Alpha Shapes., , , , , and . IEEE Trans. Med. Imaging, 35 (11): 2393-2402 (2016)Semi-automatic assessment of pediatric hydronephrosis severity in 3D ultrasound., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97851Q. SPIE, (2016)