JOURNAL ARTICLE

Medical Image Segmentation Based on 3D U-net

Abstract

For medical image processing, as the target area of the tumor lesions is small, and the boundaries of the organs are blurred, so the segmentation of the medical images is difficult. In the original 3D U-net model, feature extraction is performed on the interest image region by increasing the channel attention mechanism, so that the model keep a watchful eye on key region before segmentation. Test results indicate that the improved model has significantly improved segmentation accuracy relative to the original 3D U-net model and is a valid image segmentation model.

Keywords:
Image segmentation Artificial intelligence Computer science Segmentation Scale-space segmentation Computer vision Segmentation-based object categorization Region growing Image (mathematics) Pattern recognition (psychology) Feature (linguistics) Minimum spanning tree-based segmentation

Metrics

6
Cited By
0.63
FWCI (Field Weighted Citation Impact)
7
Refs
0.70
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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