UNet++: A Nested U-Net Architecture for Medical Image Segmentation [PDF]
DLMIA/ML-CDS@MICCAI, 2018 In this paper, we present UNet++, a new, more powerful architecture for medical image segmentation. Our architecture is essentially a deeply-supervised encoder-decoder network where the encoder and decoder sub-networks are connected through a series of ...
Liang, Jianming +3 more
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Implementation of CT Image Segmentation Based on an Image Segmentation Algorithm
Applied Bionics and Biomechanics, 2022 With the increasingly important role of image segmentation in the field of computed tomography (CT) image segmentation, the requirements for image segmentation technology in related industries are constantly improving.
Lingli Shen
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nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Nature Methods, 2020 Fabian Isensee +2 more
exaly +2 more sources
Survey on Image Panoptic Segmentation Based on Deep Learning [PDF]
Jisuanji kexue yu tansuo, 2023 With the continuous development of deep learning and image segmentation, image panoptic segmentation has become a research hotspot in the field of computer vision, and many image panoptic segmentation methods have been proposed. This paper summarizes the
BI Yangyang, ZHENG Yuanfan, SHI Caijuan, ZHANG Kun, LIU Jian
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Survey Progress on Image Instance Segmentation Methods of Deep Convolutional Neural Network [PDF]
Jisuanji kexue, 2022 Image instance segmentation is an important part of image processing and computer vision technology about image understanding.With the development of deep learning and deep convolutional neural network,image instance segmentation method based on deep ...
HU Fu-yuan, WAN Xin-jun, SHEN Ming-fei, XU Jiang-lang, YAO Rui, TAO Zhong-ben
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Masked-attention Mask Transformer for Universal Image Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 Image segmentation groups pixels with different semantics, e.g., category or instance membership. Each choice of semantics defines a task. While only the semantics of each task differ, current research focuses on designing spe-cialized architectures for ...
Bowen Cheng +4 more
semanticscholar +1 more source
UNETR: Transformers for 3D Medical Image Segmentation [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2021 Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image segmentation applications since the past decade. In FCNNs, the encoder plays an integral role by learning both global
Ali Hatamizadeh +3 more
semanticscholar +1 more source
Segmentation for Athlete's Ankle Injury Image Using Residual Double Attention U-Net Model [PDF]
Brazilian Archives of Biology and Technology, 2023 The image of an athlete's ankle joint injury can help to check whether the athlete's ankle joint is damaged, and plays a very important role in clinical diagnosis.
Jing Zhang +3 more
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Research Review of Image Semantic Segmentation Method in High-Resolution Remote Sensing Image Interpretation [PDF]
Jisuanji kexue yu tansuo, 2023 Rapid acquisition of remote sensing information has important research significance for the development of image semantic segmentation methods in remote sensing image interpretation applications.
MA Yan, Gulimila·Kezierbieke
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MULTIFRACTAL SEGMENTATION OF IMAGES [PDF]
Fractals, 1994 We propose a multifractal approach to the problem of image analysis. We show that an alternative description of images, based on a multifractal characterization, can be used instead of the classical approach that involves smoothing of the discrete data in order to compute local extrema.
Lévy Véhel, Jacques, Mignot, Pascal
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