Results 11 to 20 of about 151,110 (308)

Segment anything in medical images

Nature Communications
Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, Bo Wang   +5 more
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Automated medical image segmentation techniques

Journal of Medical Physics, 2010
Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment ...
Sharma Neeraj, Aggarwal Lalit
doaj   +3 more sources

Efficient Subclass Segmentation in Medical Images [PDF]

, 2023
As research interests in medical image analysis become increasingly fine-grained, the cost for extensive annotation also rises. One feasible way to reduce the cost is to annotate with coarse-grained superclass labels while using limited fine-grained annotations as a complement.
Linrui Dai, Wenhui Lei, Xiaofan Zhang
openalex   +3 more sources

DRINet for Medical Image Segmentation

IEEE Transactions on Medical Imaging, 2018
Convolutional neural networks (CNNs) have revolutionized medical image analysis over the past few years. The U-Net architecture is one of the most well-known CNN architectures for semantic segmentation and has achieved remarkable successes in many different medical image segmentation applications. The U-Net architecture consists of standard convolution
Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert   +5 more
openaire   +4 more sources

Trends and Techniques in Medical Image Segmentation for Disease Detection [PDF]

ITM Web of Conferences
Medical images have become an indispensable and important tool for the diagnosis of medical conditions and surgical guidance. As computer vision technology advances, Medical image segmentation technology has effectively assisted clinicians in making ...
Jiang Xinli
doaj   +1 more source

The semiotics of medical image Segmentation [PDF]

Medical Image Analysis, 2018
As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive ...
Baxter, John S.H., Gibson, Eli, Eagleson, Roy, Peters, Terry M.   +3 more
openaire   +5 more sources

A medical image segmentation method based on multi-dimensional statistical features

Frontiers in Neuroscience, 2022
Medical image segmentation has important auxiliary significance for clinical diagnosis and treatment. Most of existing medical image segmentation solutions adopt convolutional neural networks (CNNs).
Yang Xu, Xianyu He, Guofeng Xu, Guanqiu Qi, Kun Yu, Li Yin, Pan Yang, Pan Yang, Yuehui Yin, Hao Chen   +9 more
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Medical Image Segmentation Using Transformer Networks [PDF]

IEEE Access, 2022
Deep learning models represent the state of the art in medical image segmentation. Most of these models are fully-convolutional networks (FCNs), namely each layer processes the output of the preceding layer with convolution operations. The convolution operation enjoys several important properties such as sparse interactions, parameter sharing, and ...
Davood Karimi, Haoran Dou, Ali Gholipour
openaire   +3 more sources

Fully Convolutional Network for the Semantic Segmentation of Medical Images: A Survey

Diagnostics, 2022
There have been major developments in deep learning in computer vision since the 2010s. Deep learning has contributed to a wealth of data in medical image processing, and semantic segmentation is a salient technique in this field.
Sheng-Yao Huang, Wen-Lin Hsu, Ren-Jun Hsu, Dai-Wei Liu   +3 more
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Review of U-Net-Based Convolutional Neural Networks for Breast Medical Image Segmentation [PDF]

Jisuanji kexue yu tansuo
U-Net and its variants have showcased exceptional performance in the domain of breast medical image segmentation. By employing a fully convolutional network (FCN) structure for semantic segmentation, the symmetrical structure of U-Net offers remarkable ...
PU Qiumei, YIN Shuai, LI Zhengmao, ZHAO Lina
doaj   +1 more source