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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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Customized Segment Anything Model for Medical Image Segmentation [PDF]
arXiv.org, 2023 We propose SAMed, a general solution for medical image segmentation. Different from the previous methods, SAMed is built upon the large-scale image segmentation model, Segment Anything Model (SAM), to explore the new research paradigm of customizing ...
Kaiwen Zhang, Dong Liu
semanticscholar +1 more source
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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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. +3 more
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì +2 more
semanticscholar +1 more source
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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CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation [PDF]
International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021 Convolutional neural networks (CNNs) have been the de facto standard for nowadays 3D medical image segmentation. The convolutional operations used in these networks, however, inevitably have limitations in modeling the long-range dependency due to their ...
Yutong Xie +3 more
semanticscholar +1 more source
Robust T-Loss for Medical Image Segmentation
Medical Image Analysis, 2023 This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution and can effectively handle outliers in the data by controlling its sensitivity with a single parameter.
Alvaro Gonzalez-Jimenez +5 more
openaire +2 more sources
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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CE-Net: Context Encoder Network for 2D Medical Image Segmentation [PDF]
IEEE Transactions on Medical Imaging, 2019 Medical image segmentation is an important step in medical image analysis. With the rapid development of a convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation ...
Zaiwang Gu +8 more
semanticscholar +1 more source