A novel MRI segmentation method using CNN‐based correction network for MRI‐guided adaptive radiotherapy
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Yonggang Lu | Xue Wu | Deshan Yang | Xiao Chang | Thomas R Mazur | Yabo Fu | Shi Liu | H Harold Li | Hyun Kim | Michael C Roach | Lauren Henke | Yonggang Lu | Deshan Yang | M. Roach | Yabo Fu | T. Mazur | L. Henke | H. Li | Shi Liu | X. Chang | Hyun Kim | Xue Wu | H. H. Li | Michael C. Roach
[1] Fang Lu,et al. Automatic 3D liver location and segmentation via convolutional neural network and graph cut , 2016, International Journal of Computer Assisted Radiology and Surgery.
[2] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Sasa Mutic,et al. The ViewRay system: magnetic resonance-guided and controlled radiotherapy. , 2014, Seminars in radiation oncology.
[4] Vladlen Koltun,et al. Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials , 2011, NIPS.
[5] Bram van Ginneken,et al. A survey on deep learning in medical image analysis , 2017, Medical Image Anal..
[6] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[7] Hao Chen,et al. VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images , 2017, NeuroImage.
[8] Paolo Zaffino,et al. Deep Neural Networks for Fast Segmentation of 3D Medical Images , 2016, MICCAI.
[9] Iasonas Kokkinos,et al. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Sebastian Nowozin,et al. Stabilizing Training of Generative Adversarial Networks through Regularization , 2017, NIPS.
[11] Jose Dolz,et al. 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study , 2016, NeuroImage.
[12] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[13] Konstantinos Kamnitsas,et al. Efficient multi‐scale 3D CNN with fully connected CRF for accurate brain lesion segmentation , 2016, Medical Image Anal..
[14] Guosheng Lin,et al. Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Sasa Mutic,et al. Benchmark IMRT evaluation of a Co-60 MRI-guided radiation therapy system. , 2015, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.
[16] Jialin Peng,et al. Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution , 2016, Physics in medicine and biology.
[17] Xiangrong Zhou,et al. Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method , 2017, Medical physics.
[18] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[19] Atsuto Maki,et al. A systematic study of the class imbalance problem in convolutional neural networks , 2017, Neural Networks.
[20] Seyed-Ahmad Ahmadi,et al. Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields , 2016, MICCAI.
[21] Parag J Parikh,et al. Segmentation precision of abdominal anatomy for MRI-based radiotherapy. , 2014, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.
[22] Tao Xu,et al. SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation , 2017, Neuroinformatics.
[23] 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).
[24] Iasonas Kokkinos,et al. Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs , 2014, ICLR.
[25] Lin Yang,et al. An Automatic Learning-Based Framework for Robust Nucleus Segmentation , 2016, IEEE Transactions on Medical Imaging.
[26] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[27] Sasa Mutic,et al. Quality of Intensity Modulated Radiation Therapy Treatment Plans Using a ⁶⁰Co Magnetic Resonance Image Guidance Radiation Therapy System. , 2015, International journal of radiation oncology, biology, physics.
[28] Max A. Viergever,et al. Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities , 2016, MICCAI.
[29] Minsong Cao,et al. Online Adaptive Radiation Therapy: Implementation of a New Process of Care , 2017, Cureus.
[30] Lin Yang,et al. Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[31] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[32] Thomas Brox,et al. Generating Images with Perceptual Similarity Metrics based on Deep Networks , 2016, NIPS.
[33] Thomas Brox,et al. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation , 2016, MICCAI.
[34] M. Viergever,et al. Automatic Segmentation of MR Brain Images With a Convolutional Neural Network. , 2016, IEEE transactions on medical imaging.
[35] Hao Chen,et al. Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets , 2017, MICCAI.
[36] Hao Chen,et al. 3D deeply supervised network for automated segmentation of volumetric medical images , 2017, Medical Image Anal..
[37] Sebastian Nowozin,et al. Which Training Methods for GANs do actually Converge? , 2018, ICML.
[38] Daniel P. Huttenlocher,et al. Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..