Abstract is missing.
- Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 ChallengeLeon Weninger, Oliver Rippel, Simon Koppers, Dorit Merhof. 3-12 [doi]
- Segmenting Brain Tumors from MRI Using Cascaded Multi-modal U-NetsMichal Marcinkiewicz, Jakub Nalepa, Pablo Ribalta Lorenzo, Wojciech Dudzik, Grzegorz Mrukwa. 13-24 [doi]
- Automatic Brain Tumor Segmentation by Exploring the Multi-modality Complementary Information and Cascaded 3D Lightweight CNNsJun Ma, Xiaoping Yang. 25-36 [doi]
- Deep Convolutional Neural Networks Using U-Net for Automatic Brain Tumor Segmentation in Multimodal MRI VolumesAdel Kermi, Issam Mahmoudi, Mohamed Tarek Khadir. 37-48 [doi]
- Multimodal Brain Tumor Segmentation Using Cascaded V-NetsRui Hua, Quan Huo, Yaozong Gao, Yu Sun, Feng Shi. 49-60 [doi]
- Automatic Brain Tumor Segmentation Using Convolutional Neural Networks with Test-Time AugmentationGuotai Wang, Wenqi Li, Sébastien Ourselin, Tom Vercauteren. 61-72 [doi]
- Extending 2D Deep Learning Architectures to 3D Image Segmentation ProblemsAlberto Albiol, Antonio Albiol, Francisco Albiol. 73-82 [doi]
- Tumor Segmentation and Survival Prediction in Glioma with Deep LearningLi Sun, Songtao Zhang, Lin Luo. 83-93 [doi]
- Multi-planar Spatial-ConvNet for Segmentation and Survival Prediction in Brain CancerSubhashis Banerjee, Sushmita Mitra, B. Uma Shankar. 94-104 [doi]
- A Pretrained DenseNet Encoder for Brain Tumor SegmentationJean Stawiaski. 105-115 [doi]
- Hierarchical Multi-class Segmentation of Glioma Images Using Networks with Multi-level Activation FunctionXiaobin Hu, Hongwei Li, Yu Zhao, Chao Dong, Bjoern H. Menze, Marie Piraud. 116-127 [doi]
- Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival PredictionPo-Yu Kao, Thuyen Ngo, Angela Zhang, Jefferson W. Chen, B. S. Manjunath. 128-141 [doi]
- Glioma Prognosis: Segmentation of the Tumor and Survival Prediction Using Shape, Geometric and Clinical InformationMobarakol Islam, V. Jeya Maria Jose, Hongliang Ren 0001. 142-153 [doi]
- Segmentation of Brain Tumors Using DeepLabv3+Ahana Roy Choudhury, Rami Vanguri, Sachin R. Jambawalikar, Piyush Kumar. 154-167 [doi]
- Brain Tumor Segmentation on Multimodal MR Imaging Using Multi-level Upsampling in DecoderYan Hu, Xiang Liu, Xin Wen, Chen Niu, Yong Xia. 168-177 [doi]
- Neuromorphic Neural Network for Multimodal Brain Image Segmentation and Overall Survival AnalysisWoo-Sup Han, Il Song Han. 178-188 [doi]
- Glioma Segmentation with Cascaded UNetDmitry Lachinov, Evgeny Vasiliev, Vadim Turlapov. 189-198 [doi]
- Segmentation of Gliomas and Prediction of Patient Overall Survival: A Simple and Fast ProcedureÉlodie Puybareau, Guillaume Tochon, Joseph Chazalon, Jonathan Fabrizio. 199-209 [doi]
- Brain Tumour Segmentation Method Based on Supervoxels and Sparse DictionariesJ. P. Serrano-Rubio, Richard Everson. 210-221 [doi]
- Multi-scale Masked 3-D U-Net for Brain Tumor SegmentationYanwu Xu, Mingming Gong, Huan Fu, Dacheng Tao, Kun Zhang, Kayhan Batmanghelich. 222-233 [doi]
- No New-NetFabian Isensee, Philipp Kickingereder, Wolfgang Wick, Martin Bendszus, Klaus H. Maier-Hein. 234-244 [doi]
- 3D-ESPNet with Pyramidal Refinement for Volumetric Brain Tumor Image SegmentationNicholas Nuechterlein, Sachin Mehta. 245-253 [doi]
- 3D U-Net for Brain Tumour SegmentationRaghav Mehta, Tal Arbel. 254-266 [doi]
- Automatic Brain Tumor Segmentation with Contour Aware Residual Network and Adversarial TrainingHao-Yu Yang, Junlin Yang. 267-278 [doi]
- Brain Tumor Segmentation Using an Ensemble of 3D U-Nets and Overall Survival Prediction Using Radiomic FeaturesXue Feng, Nicholas J. Tustison, Craig H. Meyer. 279-288 [doi]
- A Novel Domain Adaptation Framework for Medical Image SegmentationAmir Gholami, Shashank Subramanian, Varun Shenoy, Naveen Himthani, Xiangyu Yue, Sicheng Zhao, Peter H. Jin, George Biros, Kurt Keutzer. 289-298 [doi]
- Context Aware 3D CNNs for Brain Tumor SegmentationSiddhartha Chandra, Maria Vakalopoulou, Lucas Fidon, Enzo Battistella, Théo Estienne, Roger Sun, Charlotte Robert, Eric Deutsch, Nikos Paragios. 299-310 [doi]
- 3D MRI Brain Tumor Segmentation Using Autoencoder RegularizationAndriy Myronenko. 311-320 [doi]
- voxel-GAN: Adversarial Framework for Learning Imbalanced Brain Tumor SegmentationMina Rezaei, Haojin Yang, Christoph Meinel. 321-333 [doi]
- Brain Tumor Segmentation and Survival Prediction Using a Cascade of Random ForestsSzidónia Lefkovits, László Szilágyi, László Lefkovits. 334-345 [doi]
- Automatic Segmentation of Brain Tumor Using 3D SE-Inception Networks with Residual ConnectionsHongdou Yao, Xiaobing Zhou, Xuejie Zhang. 346-357 [doi]
- S3D-UNet: Separable 3D U-Net for Brain Tumor SegmentationWei Chen 0039, Boqiang Liu, Suting Peng, Jiawei Sun, Xu Qiao. 358-368 [doi]
- Deep Learning Radiomics Algorithm for Gliomas (DRAG) Model: A Novel Approach Using 3D UNET Based Deep Convolutional Neural Network for Predicting Survival in GliomasUjjwal Baid, Sanjay Talbar, Swapnil Rane, Sudeep Gupta, Meenakshi H. Thakur, Aliasgar Moiyadi, Siddhesh Thakur, Abhishek Mahajan. 369-379 [doi]
- Automatic Brain Tumor Segmentation with Domain AdaptationLutao Dai, Tengfei Li, Hai Shu, Liming Zhong, Haipeng Shen, Hongtu Zhu. 380-392 [doi]
- Global Planar Convolutions for Improved Context Aggregation in Brain Tumor SegmentationSanti Puch, Irina Sánchez, Aura Hernández, Gemma Piella, Vesna Prckovska. 393-405 [doi]
- Automatic Brain Tumor Segmentation and Overall Survival Prediction Using Machine Learning AlgorithmsEric Carver, Chang Liu, Weiwei Zong, Zhenzhen Dai, James M. Snyder, Joon Lee, Ning Wen. 406-418 [doi]
- Deep Hourglass for Brain Tumor SegmentationEze Benson, Michael P. Pound, Andrew P. French, Aaron S. Jackson, Tony P. Pridmore. 419-428 [doi]
- Deep Learning Versus Classical Regression for Brain Tumor Patient Survival PredictionYannick Suter, Alain Jungo, Michael Rebsamen, Urspeter Knecht, Evelyn Herrmann, Roland Wiest, Mauricio Reyes 0001. 429-440 [doi]
- Semi-automatic Brain Tumor Segmentation by Drawing Long Axes on Multi-plane ReformatDavid Gering, Kay Sun, Aaron Avery, Roger Chylla, Ajeet Vivekanandan, Lisa Kohli, Haley Knapp, Brad Paschke, Brett Young-Moxon, Nik King, Thomas Mackie. 441-455 [doi]
- Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor SegmentationRichard McKinley, Raphael Meier, Roland Wiest. 456-465 [doi]
- Brain Tumor Segmentation Using Bit-plane and UNETTran Anh Tuan, Tran Anh Tuan, Pham The Bao. 466-475 [doi]
- Glioma Segmentation and a Simple Accurate Model for Overall Survival PredictionEvan Gates, J. Gregory Pauloski, Dawid Schellingerhout, David Fuentes. 476-484 [doi]
- Ensemble of Fully Convolutional Neural Network for Brain Tumor Segmentation from Magnetic Resonance ImagesAvinash Kori, Mehul Soni, B. Pranjal, Mahendra Khened, Alex Varghese, Ganapathy Krishnamurthi. 485-496 [doi]
- Learning Contextual and Attentive Information for Brain Tumor SegmentationChenhong Zhou, Shengcong Chen, Changxing Ding, Dacheng Tao. 497-507 [doi]
- Glioblastoma Survival PredictionZeina A. Shboul, Mahbubul Alam, Lasitha Vidyaratne, Linmin Pei, Khan M. Iftekharuddin. 508-515 [doi]