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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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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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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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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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Medical Image Segmentation Based on Transformer and HarDNet Structures
IEEE Access, 2023 Medical image segmentation is a crucial way to assist doctors in the accurate diagnosis of diseases. However, the accuracy of medical image segmentation needs further improvement due to the problems of many noisy medical images and the high similarity ...
Tongping Shen, Huanqing Xu
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SW-UNet: a U-Net fusing sliding window transformer block with CNN for segmentation of lung nodules
Frontiers in Medicine, 2023 Medical images are information carriers that visually reflect and record the anatomical structure of the human body, and play an important role in clinical diagnosis, teaching and research, etc.
Jiajun Ma +4 more
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Complexity, 2020 Medical image segmentation is a key technology for image guidance. Therefore, the advantages and disadvantages of image segmentation play an important role in image-guided surgery.
Feng-Ping An, Jun-e Liu
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Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels [PDF]
, 2022 Recent work has shown that label-efficient few-shot learning through self-supervision can achieve promising medical image segmentation results. However, few-shot segmentation models typically rely on prototype representations of the semantic classes ...
Jenssen, Robert +3 more
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