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Hybrid intelligence in medical image segmentation. [PDF]
Sci RepAbstract Medical image segmentation is vital for precise identification and analysis of anatomical structures and pathological regions, yet traditional models often fall short in aligning with clinical workflows, requiring extensive manual correction even when overall segmentation accuracy is high.
Ali NM +4 more
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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
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A review: Deep learning for medical image segmentation using multi-modality fusion
Array, 2019 Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing multi-information to improve the segmentation.
Tongxue Zhou, Su Ruan, Stéphane Canu
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Frontiers in Bioengineering and BiotechnologyAccurate medical image segmentation is critical for disease quantification and treatment evaluation. While traditional U-Net architectures and their transformer-integrated variants excel in automated segmentation tasks. Existing models also struggle with
Guanqun Sun +10 more
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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
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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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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
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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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A Survey on Medical Image Segmentation Based on Deep Learning Techniques
Big Data and Cognitive Computing, 2022 Deep learning techniques have rapidly become important as a preferred method for evaluating medical image segmentation. This survey analyses different contributions in the deep learning medical field, including the major common issues published in recent
Jayashree Moorthy, Usha Devi Gandhi
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Fast Segmentation of Vertebrae CT Image Based on the SNIC Algorithm
Tomography, 2022 Automatic image segmentation plays an important role in the fields of medical image processing so that these fields constantly put forward higher requirements for the accuracy and speed of segmentation.
Bing Li +4 more
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