Table of Contents

• A Review of Medical Federated Learning: Applications in Oncology and Cancer ResearchAlexander Chowdhury, Hasan Kassem, Nicolas Padoy, Renato Umeton, Alexandros Karargyris. 3-24 [doi]
• Opportunities and Challenges for Deep Learning in Brain LesionsJay B. Patel, Ken Chang, Syed Rakin Ahmed, Ikbeom Jang, Jayashree Kalpathy-Cramer. 25-36 [doi]
• EMSViT: Efficient Multi Scale Vision Transformer for Biomedical Image SegmentationAbhinav Sagar. 39-51 [doi]
• CA-Net: Collaborative Attention Network for Multi-modal Diagnosis of GliomasBaocai Yin, Hu Cheng, Fengyan Wang, Zengfu Wang. 52-62 [doi]
• Challenging Current Semi-supervised Anomaly Segmentation Methods for Brain MRIFelix Meissen, Georgios Kaissis, Daniel Rueckert. 63-74 [doi]
• Small Lesion Segmentation in Brain MRIs with Subpixel EmbeddingAlex Wong 0001, Allison Chen, Yangchao Wu, Safa Cicek, Alexandre Tiard, Byung-Woo Hong, Stefano Soatto. 75-87 [doi]
• Unsupervised Multimodal Supervoxel Merging Towards Brain Tumor SegmentationGuillaume Pelluet, Mira Rizkallah, Oscar Acosta, Diana Mateus. 88-99 [doi]
• Evaluating Glioma Growth Predictions as a Forward Ranking ProblemKarin A. van Garderen, Sebastian R. van der Voort, Maarten M. J. Wijnenga, Fatih Incekara, Georgios Kapsas, Renske Gahrmann, Ahmad Alafandi, Marion Smits, Stefan Klein 0001. 100-111 [doi]
• Modeling Multi-annotator Uncertainty as Multi-class Segmentation ProblemMartin Zukovec, Lara Dular, Ziga Spiclin. 112-123 [doi]
• Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for GlioblastomaYifan Li, Chao Li 0031, Yiran Wei 0002, Stephen J. Price, Carola-Bibiane Schönlieb, Xi Chen 0042. 124-139 [doi]
• Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural NetworksYiran Wei 0002, Yonghao Li, Xi Chen 0042, Carola-Bibiane Schönlieb, Chao Li 0031, Stephen J. Price. 140-150 [doi]
• Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource EnvironmentsSiddhesh P. Thakur, Sarthak Pati, Ravi Panchumarthy, Deepthi Karkada, Junwen Wu, Dmitry Kurtaev, Chiharu Sako, Prashant Shah, Spyridon Bakas. 151-167 [doi]
• Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation TaskHimashi Peiris, Zhaolin Chen, Gary F. Egan, Mehrtash Harandi. 171-181 [doi]
• Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor SegmentationAgus Subhan Akbar, Chastine Fatichah, Nanik Suciati. 182-193 [doi]
• BRATS2021: Exploring Each Sequence in Multi-modal Input for Baseline U-net PerformancePolina Druzhinina, Ekaterina Kondrateva, Arseny Bozhenko, Vyacheslav Yarkin, Maxim Sharaev, Anvar Kurmukov. 194-203 [doi]
• Combining Global Information with Topological Prior for Brain Tumor SegmentationHua Yang, Zhiqiang Shen, Zhaopei Li, Jinqing Liu, Jinchao Xiao. 204-215 [doi]
• Automatic Brain Tumor Segmentation Using Multi-scale Features and Attention MechanismZhaopei Li, Zhiqiang Shen, Jianhui Wen, Tian He, Lin Pan. 216-226 [doi]
• Simple and Fast Convolutional Neural Network Applied to Median Cross Sections for Predicting the Presence of MGMT Promoter Methylation in FLAIR MRI ScansDaniel Tianming Chen, Allen Tianle Chen, Haiyan Wang. 227-238 [doi]
• Brain Tumor Segmentation Using Non-local Mask R-CNN and Single Model EnsembleZhenzhen Dai, Ning Wen, Eric Nathan Carver. 239-248 [doi]
• EfficientNet for Brain-Lesion ClassificationQuoc-Huy Trinh, Trong-Hieu Nguyen Mau, Radmir Zosimov, Minh Van Nguyen. 249-260 [doi]
• HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor SegmentationHung-Yu Wu, Youn-Long Lin. 261-271 [doi]
• Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI ImagesAli Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang 0005, Holger R. Roth, Daguang Xu. 272-284 [doi]
• Multi-plane UNet++ Ensemble for Glioblastoma SegmentationJohannes Roth, Johannes Keller 0006, Stefan Franke, Thomas Neumuth, Daniel Schneider. 285-294 [doi]
• Multimodal Brain Tumor Segmentation Using Modified UNet ArchitectureGaurav Singh, Ashish Phophalia. 295-305 [doi]
• A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR ImagesDaniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens, Stefan Bartzsch. 306-314 [doi]
• Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021Linmin Pei, Yanling Liu. 315-323 [doi]
• 3D MRI Brain Tumour Segmentation with Autoencoder Regularization and Hausdorff Distance Loss FunctionVladimir S. Fonov, Pedro Rosa-Neto, D. Louis Collins. 324-332 [doi]
• 3D CMM-Net with Deeper Encoder for Semantic Segmentation of Brain Tumors in BraTS2021 ChallengeYoonseok Choi, Mohammed A. Al-masni, Dong-hyun Kim. 333-343 [doi]
• Multi Modal Fusion for Radiogenomics Classification of Brain TumorTimothy Sum Hon Mun, Simon J. Doran, Paul Huang, Christina Messiou, Matthew D. Blackledge. 344-355 [doi]
• A Joint Graph and Image Convolution Network for Automatic Brain Tumor SegmentationCamillo Saueressig, Adam Berkley, Reshma Munbodh, Ritambhara Singh. 356-365 [doi]
• Brain Tumor Segmentation Using Neural Network Topology SearchAlexandre Milesi, Michal Futrega, Michal Marcinkiewicz, Pablo Ribalta. 366-376 [doi]
• Segmenting Brain Tumors in Multi-modal MRI Scans Using a 3D SegNet ArchitectureNabil Jabareen, Soeren Lukassen. 377-388 [doi]
• Residual 3D U-Net with Localization for Brain Tumor SegmentationMarc Demoustier, Ines Khemir, Quoc Duong Nguyen, Lucien Martin-Gaffé, Nicolas Boutry. 389-399 [doi]
• A Two-Phase Optimal Mass Transportation Technique for 3D Brain Tumor Detection and SegmentationWen-Wei Lin, Tiexiang Li, Tsung-Ming Huang, Jia-Wei Lin, Mei-Heng Yueh, Shing-Tung Yau. 400-409 [doi]
• Cascaded Training Pipeline for 3D Brain Tumor SegmentationMinh Sao Khue Luu, Evgeniy N. Pavlovskiy. 410-420 [doi]
• NnUNet with Region-based Training and Loss Ensembles for Brain Tumor SegmentationJun Ma, Jianan Chen 0001. 421-430 [doi]
• Brain Tumor Segmentation Using Attention Activated U-Net with Positive MiningHar Shwinder Singh. 431-440 [doi]
• Hierarchical and Global Modality Interaction for Brain Tumor SegmentationYang Yang, Shuhang Wei, Dingwen Zhang, Qingsen Yan, Shijie Zhao, Junwei Han. 441-450 [doi]
• Ensemble Outperforms Single Models in Brain Tumor SegmentationJianxun Ren, Wei Zhang, Ning An, Qingyu Hu, Youjia Zhang, Ying Zhou. 451-462 [doi]
• Brain Tumor Segmentation Using UNet-Context Encoding NetworkMd Monibor Rahman, Md. Shibly Sadique, Ahmed Temtam, Walia Farzana, L. Vidyaratne, Khan M. Iftekharuddin. 463-472 [doi]
• Ensemble CNN Networks for GBM Tumors Segmentation Using Multi-parametric MRIRamy A. Zeineldin, Mohamed E. Karar, Franziska Mathis-Ullrich, Oliver Burgert. 473-483 [doi]