科研成果详情

题名Tiny Object Detector for Pulmonary Nodules based on YOLO
作者
发表日期2023
会议名称2023 7th International Conference on Deep Learning Technologies, ICDLT 2023
会议录名称ICDLT '23: Proceedings of the 2023 7th International Conference on Deep Learning Technologies
ISBN9798400707520
页码27-34
会议日期27 July 2023 through 29 July 2023
会议地点Dalian
会议举办国China
出版地New York, United States
出版者Association for Computing Machinery
摘要

Accurate detection and discovery of early lung cancer is the most effective measure to reduce lung cancer mortality with high clinical value. However, existing common object detectors show unsatisfactory detection accuracy for pulmonary nodule detection, due to the textureless appearance and small size of nodules. To address the textureless appearance problem, we propose a dedicated Nodule-Learning C3 module, which helps to extract more informative structures from limited textures of nodules. Considering that nodules' sizes are small, we further design a tiny object detection layer that performs object detection on larger feature maps, where more nodule features are preserved. Moreover, the balance between speed and accuracy is also critical for the pulmonary nodule diagnostic system. Therefore, we choose the famous one-stage detection framework YOLO [13] as our baseline and implement our proposed module and layer based on it. Extensive experimental results on the widely used benchmark LUNA16 demonstrate the superior performance of our method, in terms of both accuracy and speed. Specifically, our model improves the mAP accuracy by over and is faster than the YOLO baseline. © 2023 ACM.

关键词LUNA16 Pulmonary Nodule Detection Tiny Object Detection YOLO
DOI10.1145/3613330.3613337
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语种英语English
Scopus入藏号2-s2.0-85175787189
引用统计
文献类型会议论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/11534
专题理工科技学院
通讯作者Zhang, Hui
作者单位
1.Department of Computer Science and Technology, Beijing Normal University-Hong Kong Baptist University United International College, China
2.Department of Computer Science, Hong Kong Baptist University, China
第一作者单位北师香港浸会大学
通讯作者单位北师香港浸会大学
推荐引用方式
GB/T 7714
Lin, Zhe,Jie, Leiping,Zhang, Hui. Tiny Object Detector for Pulmonary Nodules based on YOLO[C]. New York, United States: Association for Computing Machinery, 2023: 27-34.
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