Automatic detection method of intracranial aneurysms on maximum intensity projection images based on SE-CaraNet
白培瑞 1宋雪峰 1刘庆一 1刘佳慧 1成锦 1修晓娜 1任延德 2王成健2
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作者信息
1. 山东科技大学电子信息工程学院(山东青岛 266590)
2. 青岛大学附属医院放射科(山东青岛 265000)
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摘要
传统的单一方位最大密度投影(MIP)图像在检测颅内动脉瘤时容易忽略部分形态特征,造成漏检和误检.针对该问题,本文提出一种新的基于全方位MIP图像的颅内动脉瘤检测方法.首先,对三维磁共振血管造影(MRA)图像进行全方位最大密度投影,获得MIP图像;然后,利用匹配滤波对颅内动脉瘤区域进行预定位;最后,使用Squeeze and Excitation(SE)模块对CaraNet模型进行了改进,并用改进后的模型对全方位MIP图像中的预定位区域进行检测,确定是否患有颅内动脉瘤.本文收集了 245例图像对所提方法进行了测试实验.实验结果表明本文所提方法的精确率和特异性分别可以达到93.75％和93.86％,显著提高了对MIP图像中颅内动脉瘤的检测性能.
Abstract
Conventional maximum intensity projection(MIP)images tend to ignore some morphological features in the detection of intracranial aneurysms,resulting in missed detection and misdetection.To solve this problem,a new method for intracranial aneurysm detection based on omni-directional MIP image is proposed in this paper.Firstly,the three-dimensional magnetic resonance angiography(MRA)images were projected with the maximum density in all directions to obtain the MIP images.Then,the region of intracranial aneurysm was prepositioned by matching filter.Finally,the Squeeze and Excitation(SE)module was used to improve the CaraNet model.Excitation and the improved model were used to detect the predetermined location in the omni-directional MIP image to determine whether there was intracranial aneurysm.In this paper,245 cases of images were collected to test the proposed method.The results showed that the accuracy and specificity of the proposed method could reach 93.75％and 93.86％,respectively,significantly improved the detection performance of intracranial aneurysms in MIP images.
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