Results 21 to 30 of about 7,074,171 (358)
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì +2 more
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Sensors, 2021 High-spatial-resolution images play an important role in land cover classification, and object-based image analysis (OBIA) presents a good method of processing high-spatial-resolution images.
Shuang Hao, Yuhuan Cui, Jie Wang
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Image quality and segmentation [PDF]
Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling, 2018 Algorithms for image segmentation (including object recognition and delineation) are influenced by the quality of object appearance in the image and overall image quality. However, the issue of how to perform segmentation evaluation as a function of these quality factors has not been addressed in the literature.
Gargi V, Pednekar +7 more
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OneFormer: One Transformer to Rule Universal Image Segmentation [PDF]
Computer Vision and Pattern Recognition, 2022 Universal Image Segmentation is not a new concept. Past attempts to unify image segmentation include scene parsing, panoptic segmentation, and, more recently, new panoptic architectures.
Jitesh Jain +5 more
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MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023 There has been exploding interest in embracing Transformer-based architectures for medical image segmentation. However, the lack of large-scale annotated medical datasets make achieving performances equivalent to those in natural images challenging ...
Saikat Roy +7 more
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MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer [PDF]
AAAI Conference on Artificial Intelligence, 2023 The Diffusion Probabilistic Model (DPM) has recently gained popularity in the field of computer vision, thanks to its image generation applications, such as Imagen, Latent Diffusion Models, and Stable Diffusion, which have demonstrated impressive ...
Junde Wu +4 more
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Environment Conservation Journal, 2020 Image segmentation is an essential and critical step in huge number of applications of image processing. Accuracy of image segmentation influence retrieved information for further processing in classification and other task.
Neeraj Kumari +3 more
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SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 We present a novel and practical deep fully convolutional neural network architecture for semantic pixel-wise segmentation termed SegNet. This core trainable segmentation engine consists of an encoder network, a corresponding decoder network followed by ...
Vijay Badrinarayanan +2 more
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Channel prior convolutional attention for medical image segmentation [PDF]
Comput. Biol. Medicine, 2023 Characteristics such as low contrast and significant organ shape variations are often exhibited in medical images. The improvement of segmentation performance in medical imaging is limited by the generally insufficient adaptive capabilities of existing ...
He-lu Huang +4 more
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UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation [PDF]
IEEE Transactions on Medical Imaging, 2019 The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (1) their optimal depth is apriori unknown, requiring extensive ...
Zongwei Zhou +3 more
semanticscholar +1 more source