胎儿大脑三维表面重建算法OACSTPCD
Fetal Brain Three-Dimensional Surface Reconstruction Algorithm
通过核磁共振设备获得多个离散间距的磁共振切片图像,采用CARESU_NET卷积神经网络对图像进行分割,获取胎儿大脑区域图像.采用CARESU_NET卷积神经网络对间断切片进行边缘重构,恢复完整的边缘信息.对边缘重构后的图像组提取边缘像素,生成三维点云,运用泊松重建方法重建点云表面,得到胎儿大脑三维表面模型.结果表明:基于核磁共振图像的三维表面模型直观生动,提高诊断效率和准确性.
Multiple discrete space magnetic resonance slice images are obtained using a nuclear magnetic resonance device,a CARESU_NET convolutional neural network is used to segment image to extract the fetal brain region ima-ges.A CARESU_NET convolutional neural network is used to reconstruct edge on discontinuous slices,complete edge information is restored.A three-dimensional point clouds are generated by extracting edge pixels from the edge-reconstructed images,and the point cloud surface is reconstructed using the Poisson reconstruction method to obtain a three-dimensional surface model of the fetal brain.The results show that the three-dimensional surface model based on nuclear magnetic resonance images is intuitive and vivid,the diagnostic efficiency and accuracy are improved.
蔡凯雄;王强;陈添峰;郑力新
华侨大学工学院,福建泉州 362021泉州市妇幼保健院儿童医院,福建泉州 362000
计算机与自动化
胎儿大脑三维重建边缘重构点云处理核磁共振
fetal brainthree-dimensional reconstructionedge reconstructionpoint cloud processingnuclear mag-netic resonance
《华侨大学学报（自然科学版）》 2024 (001)
78-85 / 8
福建省科技计划项目(2020Y0039);福建省华侨大学院校联合创新项目(2022YX008)
评论