Medical Image Segmentation based on U-Net: A Review
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Abstract
Medical image analysis is performed by analyzing images obtained by medical imaging systems to solve clinical problems. The purpose is to extract effective information and improve the level of clinical diagnosis. In recent years, automatic segmentation based on deep learning (DL) methods has been widely used, where a neural network can automatically learn image features, which is in sharp contrast with the traditional manual learning method. U-net is one of the most important semantic segmentation frameworks for a convolutional neural network (CNN). It is widely used in the medical image analysis domain for lesion segmentation, anatomical segmentation, and classification. The advantage of this network…
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Topics
Keywords
- Computer science
- Segmentation
- Artificial intelligence
- Convolutional neural network
- Deep learning
- Image segmentation
- Medical imaging
- Feature (linguistics)
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