Department of Radiology and Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA;
School of Information Science and Engineering Fujian University of Technology Fuzhou 350118 China;
Department of Radiology and Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA Department of Brain and Cognitive Engineering Korea University Seoul 02841 Republic of Korea;
Neonatal brain segmentation; Multi-task learning; Attention; Geodesic distance;
机译:单通多任务网络,具有脑肿瘤分割的交叉任务引导注意
机译:基于卷积神经网络的Vivo蜂窝图像分割模型中的一种新型多相多孔
机译:一种带有多任务学习的注意力和先前嵌入的方法,用于阴影检测
机译:使用3D致密粘连的新生儿脑细分的多任务学习与测地距离引导密集的关注
机译:新生儿脑MRI结构分割和分类的计算框架
机译:Dense-UNet:一种基于卷积神经网络的新型多光子体内细胞图像分割模型
机译:基于多任务注意力的医学图像分割的半监督学习