Skip to main content

Program

8:00am: Opening Remarks – Li Wang, Gang Li, Dinggang Shen

8:00am – 8:10am: 3D U-Net baseline for iSeg-2019 and an attempt at dealing with multiple sites data via histogram matching (Team: FightAutism)
Jun Ma, Xiaoping Yang, Department of Mathematics, Nanjing University of Science and Technology

8:10am – 8:20am: Masked attention encoder-decoder networks for isointense infant brain segmentation (Team: PerceptionComputingLab_HIT)
Gongning Luo, Harbin Institute of Technology

8:20am – 8:30am: Spatially Weighted Network with Adversarial Domain Adaptation for Infant Brain MRI Segmentation (Team: SmartDSP)
Wenao Ma, Xiamen University

8:30am – 8:40am: Six-month infant brain magnetic resonance image tissue segmentation using multi-atlas segmentation with joint label fusion and convolutional neural networks (Team: nic_vicorob)
Kaisar Kushibar, Universitat de Girona

8:40am – 8:50am: DRNetF : A dense residual network with few parameters for Brain Tissue Segmentation (Team: RB)
Ramesh Basnet, Concordia University, Montreal, Canada

8:50am – 9:00am: Efficient 3D Fully Convolutional Networks for 6-month Infant Brain MRI Segmentation (Team: OxfordIBME)
Hoileong Lee, University of Oxford

9:00am – 9:10am: Evaluation of adult SLANT on infant brain MRI (Team: MASI)
Bennett Landman, Associate Professor, Vanderbilt University

9:10am – 9:20am: Efficient 3D Dense U-Net with Contour Regression for 6-month Infant Brain MRI Segmentation (Team: WorldSeg)
Zhan Liu, South China University of Technology

9:20am – 9:30am: Infant Brain MRI Segmentation with Dilated Convolution Pyramid Downsampling and Self-Attention (Team: QL111111)
Lin Qi, Zhihao Lei, College of Information Science and Engineering, Northeastern University, China

9:30am: Closing