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Deep-recursive residual network for image semantic segmentation.

, , , , and . Neural Comput. Appl., 32 (16): 12935-12947 (2020)

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Accurate quantification of local changes for carotid arteries in 3D ultrasound images using convex optimization-based deformable registration., , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 978448. SPIE, (2016)Feasibility of Multiple Micro-Particle Trapping - A Simulation Study., , , and . Sensors, 15 (3): 4958-4974 (2015)Nonrigid registration of carotid ultrasound and MR images using a "twisting and bending" model., , , , , , and . Medical Imaging: Image Processing, volume 6914 of SPIE Proceedings, page 691411. SPIE, (2008)3D MR ventricle segmentation in pre-term infants with post-hemorrhagic ventricle dilation., , , , , , and . Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 941310. SPIE, (2015)Deep-recursive residual network for image semantic segmentation., , , , and . Neural Comput. Appl., 32 (16): 12935-12947 (2020)Breast lesion classification based on supersonic shear-wave elastography and automated lesion segmentation from B-mode ultrasound images., , , and . Comput. Biol. Medicine, (2018)A Non-Rigid Image Registration Technique for 3D Ultrasound Carotid Images using a "Twisting and Bending" Model., , , , , and . EMBC, page 2738-2741. IEEE, (2006)Vessel wall segmentation of common carotid artery via multi-branch light network., , , , , and . Medical Imaging: Image Processing, volume 11313 of SPIE Proceedings, page 1131311. SPIE, (2020)A "Twisting and Bending" Model-Based Nonrigid Image Registration Technique for 3-D Ultrasound Carotid Images., , , , , and . IEEE Trans. Med. Imaging, 27 (10): 1378-1388 (2008)Modeling hemodynamic forces in carotid artery based on local geometric features., , , and . Medical Biol. Eng. Comput., 54 (9): 1437-1452 (2016)