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1. Design of Treatments for Overcoming Drug Resistance in Glioblastoma Cultures with a Mathematical Model of Cellular Adaptation

2. 3D Inception-Based TransMorph: Pre- and Post-operative Multi-contrast MRI Registration in Brain Tumors

3. Brain Tumor Segmentation Using Neural Ordinary Differential Equations with UNet-Context Encoding Network

5. Ensemble CNN Networks for GBM Tumors Segmentation Using Multi-parametric MRI

6. Adaptive Unsupervised Learning with Enhanced Feature Representation for Intra-tumor Partitioning and Survival Prediction for Glioblastoma

7. Simple and Fast Convolutional Neural Network Applied to Median Cross Sections for Predicting the Presence of MGMT Promoter Methylation in FLAIR MRI Scans

9. Brain Tumor Segmentation in Multi-parametric Magnetic Resonance Imaging Using Model Ensembling and Super-resolution

10. Brain Tumor Segmentation Using UNet-Context Encoding Network

12. A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR Images

13. Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments

15. MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks

16. Radiogenomic Prediction of MGMT Using Deep Learning with Bayesian Optimized Hyperparameters

17. Modified MobileNet for Patient Survival Prediction

18. Overall Survival Prediction for Glioblastoma on Pre-treatment MRI Using Robust Radiomics and Priors

19. Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression

20. Computational Diagnostics of GBM Tumors in the Era of Radiomics and Radiogenomics

21. Using Separated Inputs for Multimodal Brain Tumor Segmentation with 3D U-Net-like Architectures

22. The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

23. Brain Tumor Segmentation Based on 3D Residual U-Net

24. A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information

25. Towards Population-Based Histologic Stain Normalization of Glioblastoma

26. Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning

27. No New-Net

28. Glioma Segmentation and a Simple Accurate Model for Overall Survival Prediction

29. Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns

30. Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge

31. Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

32. Glioblastoma and Survival Prediction

33. A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images

34. Rotation Clustering: A Consensus Clustering Approach to Cluster Gene Expression Data

35. Improving Boundary Classification for Brain Tumor Segmentation and Longitudinal Disease Progression

36. Brain Tumor Segmentation by Variability Characterization of Tumor Boundaries

37. An Online Platform for the Automatic Reporting of Multi-parametric Tissue Signatures: A Case Study in Glioblastoma

39. Deep Active Learning for Glioblastoma Quantification

40. 'Older and Younger People': Towards a Cross-Generational Online Peer Support About Cancer. The Example of Glioblastoma on French Digital Platforms

41. Glioblastoma Multiforme Patient Survival Prediction

42. A Clinical Measuring Platform for Building the Bridge Across the Quantification of Pathological N-Cells in Medical Imaging for Studies of Disease

43. Pre-operative Overall Survival Time Prediction for Glioblastoma Patients Using Deep Learning on Both Imaging Phenotype and Genotype

44. Gene- and Pathway-Based Deep Neural Network for Multi-omics Data Integration to Predict Cancer Survival Outcomes

46. Simulating Cancer Radiotherapy on a Multi-level Basis: Biology, Oncology and Image Processing