Vicomtech Foundation and Biodonostia, San Sebastian, Spain,BCN Medtech, Universitat Pompeu Fabra, Barcelona, Spain,Applied Chest Imaging Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Applied Chest Imaging Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Applied Chest Imaging Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Applied Chest Imaging Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Vicomtech Foundation and Biodonostia, San Sebastian, Spain;
BCN Medtech, Universitat Pompeu Fabra, Barcelona, Spain,ICREA, Barcelona, Spain;
Applied Chest Imaging Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA;
Pulmonary artery; Deep learning; CTA Convolutional neural network; Segmentation;
机译:CTA数据集中肺动脉从纵隔到肺的分割
机译:在3D CTA数据集中,基于半自动水平集的颈内动脉分割和狭窄量化。
机译:PWD-3DNet:在颞骨CT扫描上的多种结构的基于深度学习的完全自动分割
机译:CTA扫描的3D肺动脉分割使用深入学习与现实数据增强
机译:从胸部CTA扫描中分离动脉和静脉,并将其应用于PE检测和体积可视化。
机译:基于小型医学图像数据集的深神经网络算法的性能:3D-2D改革与新型数据增强光度转换或转移学习结合的增量影响
机译:基于半自动水平集的3D CTA数据集中颈内动脉的分割和狭窄量化