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Danni Ai
Also published under:Dan-ni Ai
Affiliation
School of Optics and Photonics, Beijing Institute of Technology, Beijing, China
Topic
Computed Tomography,Dice Similarity Coefficient,Loss Function,Convolutional Layers,Feature Maps,Magnetic Resonance Imaging,Segmentation Results,Convolutional Neural Network,Medical Image Segmentation,Medical Imaging,Abdominal Computed Tomography,Clinical Datasets,Input Image,Liver Vessels,Point Cloud,3D U-Net,Automatic Segmentation,Average Error,Biomechanical Model,CTA Images,Chinese PLA General Hospital,Clinical Magnetic Resonance Imaging,Color Images,Computed Tomography Images,Consistency Loss,Coronary Artery,Deep Learning,Feature Extraction Capability,Flow Velocity,Generative Adversarial Networks,Hepatic Vein,High-level Features,Image Guidance,Image Registration,Intraoperative Imaging,Left Camera,Lesion Segmentation,Local Feature Extraction,Local Features,Non-rigid Deformation,Non-rigid Registration,Objective Function,PLA General Hospital,Peak Signal-to-noise Ratio,Preoperative Imaging,Public Datasets,Registration Accuracy,Registration Error,Registration Method,Respiratory Motion,
Biography
Danni Ai received the B.S. and M.S. degrees from Xi’an Jiaotong University in 2008 and 2005, respectively, and the Ph.D. degree from Ritsumeikan University, Japan, in 2011. She is currently an Associate Professor with the School of Optics and Photonics, Beijing Institute of Technology. Her research interests include medical image analysis, surgical navigation, virtual reality, and augmented reality.