| Residential College | false |
| Status | 已發表Published |
| A 3D Deep Learning-based Segmentation Model for Unified and Fully Automated Segmentation of Lungs, Normal Liver and Tumors for Y-90 Radioembolization Dosimetry | |
Gefei Chen1 ; Haiyan Wang1; Zhonglin Lu1; Ko-Han Lin2; MOK SENG PENG1 
| |
| 2024-06 | |
| Conference Name | Society of Nuclear Medicine and Molecular Imaging 2024 Annual Meeting |
| Conference Date | June 8-11, 2024 |
| Conference Place | Toronto, Canada |
| Document Type | Conference paper |
| Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
| Corresponding Author | MOK SENG PENG |
| Affiliation | 1.University of Macau 2.Taipei Veterans General Hospital |
| First Author Affilication | University of Macau |
| Corresponding Author Affilication | University of Macau |
| Recommended Citation GB/T 7714 | Gefei Chen,Haiyan Wang,Zhonglin Lu,et al. A 3D Deep Learning-based Segmentation Model for Unified and Fully Automated Segmentation of Lungs, Normal Liver and Tumors for Y-90 Radioembolization Dosimetry[C], 2024. |
| APA | Gefei Chen., Haiyan Wang., Zhonglin Lu., Ko-Han Lin., & MOK SENG PENG (2024). A 3D Deep Learning-based Segmentation Model for Unified and Fully Automated Segmentation of Lungs, Normal Liver and Tumors for Y-90 Radioembolization Dosimetry. . |
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