Xiaonan Gao, Guangyuan Zhang, Fengyü Zhou, Dexin Yu. Location Decision of Needle Entry Point Based on Improved Pruning Algorithm[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2415001
- Laser & Optoelectronics Progress
- Vol. 59, Issue 24, 2415001 (2022)
Fig. 1. Vein detection algorithm flow of semi-automatic blood collection
Fig. 2. Algorithm flow of automatic detection and annotation of dorsal hand vein injection image
Fig. 3. Structure of AT-U-NET model
Fig. 4. Non-Local structure
Fig. 5. Structure of U-Netup module
Fig. 6. Strengthened feature extraction network
Fig. 7. Original map and segmentation map of dorsal hand vein. (a) Original map; (b) segmentation map
Fig. 8. PT-Pruning flowchart
Fig. 9. Cannibalization stage
Fig. 10. Vein segmentation figure and main line of vascular skeleton. (a) Segmentation; (b) main line
Fig. 11. Decision experiment of needle entry point position
Fig. 12. Dorsal hand vein imaging acquisition equipment
Fig. 13. Original dorsal hand vein images
Fig. 14. Original pictures and label images
Fig. 15. Original pictures and label images
Fig. 16. Detection and segmentation effect of at-u-net dorsal hand vein
Fig. 17. Original back of hand
Fig. 18. Image after homomorphic filtering
Fig. 19. Image after CLAHE processing
Fig. 20. Image after adaptive threshold segmentation
Fig. 21. Image after morphological processing
Fig. 22. Image after closed operation
Fig. 23. Different semantic segmentation model processing effects
Fig. 24. Effect of PT-Pruning needle entry point position decision
Fig. 25. Optimal needle entry point position decision
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Table 1. Performance indexes of different semantic segmentation models for segmentation of dorsal hand vein
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Table 2. Accuracy of needle entry point recognition in effective area
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Table 3. Recognition accuracy of optimal needle entry point
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