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Real-time detection transformer nodule: an improved real-time detection transformer algorithm for lung nodule detection in computed tomography images

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成果类型:
期刊论文
作者:
Li, Chenyang;Deng, Jiangming;Ye, Chen;Yan, Yuanchen;Wen, Guozhi
通讯作者:
Wen, GZ
作者机构:
[Yan, Yuanchen; Wen, GZ; Ye, Chen; Wen, Guozhi; Deng, Jiangming; Li, Chenyang] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan, Peoples R China.
通讯机构:
[Wen, GZ ] W
Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan, Peoples R China.
语种:
英文
关键词:
Object detection;Lung;Convolution;Transformers;Feature fusion;Computed tomography;Cancer detection;Feature extraction;Target detection;Data modeling
期刊:
Journal of Electronic Imaging
ISSN:
1017-9909
年:
2025
卷:
34
期:
3
机构署名:
本校为第一且通讯机构
院系归属:
电气与电子工程学院
摘要:
Detecting lung nodules through computed tomography (CT) scans plays an important role in early prevention, clinical diagnosis, and monitoring of lung cancer. However, the small, irregular shape and low resolution of lung nodules, together with multiscale challenges, often hinder accurate detection, especially for small nodules. To overcome these obstacles, we propose an improved detection algorithm, a real-time detection transformer (RT-DETR) nodule, specifically for lung nodules in CT images. The proposed RT-DETR framework includes several imp...

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