Results 11 to 20 of about 274,745 (274)
U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications
IEEE Access, 2021 U-net is an image segmentation technique developed primarily for image segmentation tasks. These traits provide U-net with a high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for ...
Nahian Siddique +3 more
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Scientific Reports, 2022 Deep learning allows automatic segmentation of teeth on cone beam computed tomography (CBCT). However, the segmentation performance of deep learning varies among different training strategies.
Kang Hsu +12 more
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Frontiers in Oncology, 2021 Few studies have reported the reproducibility and stability of ultrasound (US) images based radiomics features obtained from automatic segmentation in oncology. The purpose of this study is to study the accuracy of automatic segmentation algorithms based
Juebin Jin +9 more
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UIU-Net: U-Net in U-Net for Infrared Small Object Detection
IEEE Transactions on Image Processing, 2023 Learning-based infrared small object detection methods currently rely heavily on the classification backbone network. This tends to result in tiny object loss and feature distinguishability limitations as the network depth increases. Furthermore, small objects in infrared images are frequently emerged bright and dark, posing severe demands for ...
Wu, Xin +2 more
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Journal of Medical Internet Research, 2022 BackgroundDetection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients.
Hoon Ko +7 more
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Segmentation and recognition of breast ultrasound images based on an expanded U-Net.
PLoS ONE, 2021 This paper establishes a fully automatic real-time image segmentation and recognition system for breast ultrasound intervention robots. It adopts the basic architecture of a U-shaped convolutional network (U-Net), analyses the actual application ...
Yanjun Guo +3 more
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U-Net++DSM: Improved U-Net++ for Brain Tumor Segmentation With Deep Supervision Mechanism
IEEE Access, 2023 The segmentation of brain tumors is an important and challenging content in medical image processing. Relying solely on human experts to manually segment large volumes of data can be time-consuming and delay diagnosis.
Kittipol Wisaeng
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Automated segmentation of vertebral cortex with 3D U-Net-based deep convolutional neural network
Frontiers in Bioengineering and Biotechnology, 2022 Objectives: We developed a 3D U-Net-based deep convolutional neural network for the automatic segmentation of the vertebral cortex. The purpose of this study was to evaluate the accuracy of the 3D U-Net deep learning model.Methods: In this study, a fully
Yang Li +8 more
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CROP AND WEED SEGMENTATION ON GROUND-BASED IMAGES USING DEEP CONVOLUTIONAL NEURAL NETWORK [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Weed management is of crucial importance in precision agriculture to improve productivity and reduce herbicide pollution. In this regard, showing promising results, deep learning algorithms have increasingly gained attention for crop and weed ...
H. Fathipoor, R. Shah-Hosseini, H. Arefi
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Local brain-age: A U-Net model [PDF]
Frontiers in Aging Neuroscience, 2021 AbstractWe propose a new framework for estimating neuroimaging-derived “brain-age” at a local level within the brain, using deep learning. The local approach, contrary to existing global methods, provides spatial information on anatomical patterns of brain ageing.
Sebastian G. Popescu +6 more
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