Kidney segmentation using 3D U-Net localized with Expectation Maximization
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Omid Bazgir | Luke Xie | Kai Barck | Richard A.D. Carano | Robby M. Weimer | R. Carano | R. Weimer | Luke Xie | K. Barck | Omid Bazgir
[1] Brian B. Avants,et al. An Open Source Multivariate Framework for n-Tissue Segmentation with Evaluation on Public Data , 2011, Neuroinformatics.
[2] Kyoung Mu Lee,et al. Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Chi-Wing Fu,et al. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes , 2018, IEEE Transactions on Medical Imaging.
[4] Seyed-Ahmad Ahmadi,et al. V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation , 2016, 2016 Fourth International Conference on 3D Vision (3DV).
[5] Sébastien Ourselin,et al. Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations , 2017, DLMIA/ML-CDS@MICCAI.
[6] Hao Chen,et al. VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images , 2017, NeuroImage.
[7] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.
[8] L. Schad,et al. Assessment of kidney volumes from MRI: acquisition and segmentation techniques. , 2012, AJR. American journal of roentgenology.