An Aneurysm Localization Algorithm Based on Faster R-CNN Network for Cerebral Small Vessels

作者：Yuan Meng, Xinfeng Zhang, Xiaomin Liu, Xiangsheng Li, Tianyu Zhu, Xiaoxia Chang, Jinhang Chen, Xiangyu Chen · 年份：2022 · DOI：10.1145/3581807.3581889 · 被引用次数：1 · 研究领域：Brain Tumor Detection and Classification、Advanced Neural Network Applications、Retinal Imaging and Analysis

The use of artificial intelligence algorithm to determine whether the lesion has cerebral aneurysm, especially small aneurysms, is still not completely solved. In this paper, the Faster R-CNN network was used as the localization network, and the model was trained by adjusting the network parameters, and the appropriate feature extraction network and classification network were selected to finally solve the localization problem of small aneurysms. Compared with most 3D methods, this method had the characteristics of shorter training cycle and faster image recognition. The experimental results show that the algorithm has a high accuracy in discriminating whether the lesion has cerebral aneurysm, but the false positive phenomenon may occur in the identification of single image localization. Finally, the paper discusses the experimental results and puts forward some conjecture ideas to solve the problem.