Deep learning based approach for extremity osteosarcoma segmentation in CT image(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2023年第10期
- Page:
- 1204-1211
- Research Field:
- 医学影像物理
- Publishing date:
Info
- Title:
- Deep learning based approach for extremity osteosarcoma segmentation in CT image
- Author(s):
- ZHAO Linlin1; WANG Qian1; WANG Jun2; TANG Zishuo1; LIU Yu1; FAN Zhuoming1; CHEN Jimin1
- 1. Institute of Laser Engineering, Department of Materials and Manufacturing, Beijing University of Technology, Beijing 100124, China 2. Bone and Soft Tissue Tumor Treatment Center, Peking University Peoples Hospital, Beijing 100044, China
- Keywords:
- Keywords: osteosarcoma medical image segmentation deep learning TransUNet model D-TransUNet model
- PACS:
- R318；R445.3
- DOI:
- DOI:10.3969/j.issn.1005-202X.2023.10.003
- Abstract:
- Abstract: For the task of automatic segmentation of osteosarcoma in CT images, a dataset of CT images (Osteosarcoma) is established, and a D-TransUNet model with Double-CNN feature extraction structure based on TransUNet is proposed. The 3×3 convolution kernel is used for feature extraction, and the feature channel is reduced and spliced. Finally, the image information extracted by the Double-CNN feature extraction structure is fused. The original image information extracted by the proposed model is more abundant, which further improves the segmentation accuracy.
Last Update: 2023-10-27