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Research on Medical Image Segmentation Based on SAM and Its Future Prospects [PDF]
BioengineeringThe rapid advancement of prompt-based models in natural language processing and image generation has revolutionized the field of image segmentation.
Kangxu Fan +5 more
doaj +4 more sources
DRINet for medical image segmentation [PDF]
IEEE Transactions on Medical Imaging, 2018 Convolutional neural networks (CNNs) have revolutionized medical image analysis over the past few years. The UNet architecture is one of the most well-known CNN architectures for semantic segmentation and has achieved remarkable successes in many ...
Bentley, P +5 more
core +5 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
Segment anything in medical images
Nature CommunicationsMedical 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 +5 more
doaj +4 more sources
Multi-interactive feature embedding learning for medical image segmentation [PDF]
Frontiers in MedicineMedical image segmentation task can provide the lesion object semantic information, but ignores edge texture details from the lesion region. Conversely, the medical image reconstruction task furnishes the object detailed information to facilitate the ...
Yijia Huang, Yue Luo
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Medical Image Segmentation: A Comprehensive Review of Deep Learning-Based Methods [PDF]
TomographyMedical image segmentation is a critical application of computer vision in the analysis of medical images. Its primary objective is to isolate regions of interest in medical images from the background, thereby assisting clinicians in accurately ...
Yuxiao Gao +5 more
doaj +2 more sources
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
Neural Architecture Search for Light-weight Medical Image Segmentation Network [PDF]
Jisuanji kexue, 2022 Most of the existing medical image segmentation models with excellent performance are manually designed by domain experts.The design process usually requires a lot of professional knowledge and repeated experiments.In addition,the over complex ...
ZHANG Fu-chang, ZHONG Guo-qiang, MAO Yu-xu
doaj +1 more source
A Review of Medical Image Segmentation Algorithms [PDF]
EAI Endorsed Transactions on Pervasive Health and Technology, 2021 INTRODUCTION: Image segmentation in medical physics plays a vital role in image analysis to identify the affected tumour. The process of subdividing an image into its constituent parts that are homogeneous in feature is ...
K.K.D. Ramesh +4 more
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CFM-UNet: coupling local and global feature extraction networks for medical image segmentation. [PDF]
Sci RepNiu K, Han J, Cai J.
europepmc +3 more sources