yusuke1997/dblp-id-title huggingface dataset:
Unet3D with Multiple Atrous Convolutions Attention Block for Brain Tumor Segmentation
Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation
Overall Survival Prediction Using Conventional MRI Features
Spatio-Temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation
Brain Tumor Segmentation Using Neural Network Topology Search
Brain Tumor Segmentation with Uncertainty Estimation and Overall Survival Prediction
WSSAMNet: Weakly Supervised Semantic Attentive Medical Image Registration Network
Variational-Autoencoder Regularized 3D MultiResUNet for the BraTS 2020 Brain Tumor Segmentation
Multivariate Analysis is Sufficient for Lesion-Behaviour Mapping
Brain Tumor Segmentation and Survival Prediction Using Patch Based Modified 3D U-Net
MMSSD: Multi-scale and Multi-level Single Shot Detector for Brain Metastases Detection
Multi-threshold Attention U-Net (MTAU) Based Model for Multimodal Brain Tumor Segmentation in MRI Scans
Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology
Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction
Glioma Classification Using Multimodal Radiology and Histology Data
Leveraging 2D Deep Learning ImageNet-trained Models for Native 3D Medical Image Analysis
Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task
An Unpaired Cross-Modality Segmentation Framework Using Data Augmentation and Hybrid Convolutional Networks for Segmenting Vestibular Schwannoma and Cochlea
H 2 NF-Net for Brain Tumor Segmentation Using Multimodal MR Imaging: 2nd Place Solution to BraTS Challenge 2020 Segmentation Task
Brain Tumour Segmentation on MRI Images by Voxel Classification Using Neural Networks, and Patient Survival Prediction
Extending nn-UNet for Brain Tumor Segmentation
Automatic Brain Tumor Segmentation Using Multi-scale Features and Attention Mechanism
Memory Efficient Brain Tumor Segmentation Using an Autoencoder-Regularized U-Net
Multimodal Brain Tumor Segmentation Using Modified UNet Architecture
A Two-Stage Atrous Convolution Neural Network for Brain Tumor Segmentation and Survival Prediction
Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma Segmentation
Segmentation then Prediction: A Multi-task Solution to Brain Tumor Segmentation and Survival Prediction
Unsupervised Cross-Modality Domain Adaptation for Vestibular Schwannoma Segmentation and Koos Grade Prediction Based on Semi-supervised Contrastive Learning
An Ensemble Approach to Automatic Brain Tumor Segmentation
Brain Tumor Segmentation in Multi-parametric Magnetic Resonance Imaging Using Model Ensembling and Super-resolution
Multimodal Brain Image Analysis and Survival Prediction Using Neuromorphic Attention-Based Neural Networks
Enhancing Data Diversity for Self-training Based Unsupervised Cross-Modality Vestibular Schwannoma and Cochlea Segmentation
3D Automatic Brain Tumor Segmentation Using a Multiscale Input U-Net Network
Two-Stage Cascaded U-Net: 1st Place Solution to BraTS Challenge 2019 Segmentation Task
Efficient Brain Tumour Segmentation Using Co-registered Data and Ensembles of Specialised Learners
Neural Network Based Brain Tumor Segmentation
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part I
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 9th International Workshop, BrainLes 2023, and 3rd International Workshop, SWITCH 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8 and 12, 2023, Revised Selected Papers
From Whole Slide Tissues to Knowledge: Mapping Sub-cellular Morphology of Cancer
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network
Multimodal Brain Tumor Segmentation Using a 3D ResUNet in BraTS 2021
Multi-modal Transformer for Brain Tumor Segmentation
Evaluating Scale Attention Network for Automatic Brain Tumor Segmentation with Large Multi-parametric MRI Database
Center Dropout: A Simple Method for Speed and Fairness in Federated Learning
Comparison of MR Preprocessing Strategies and Sequences for Radiomics-Based MGMT Prediction
Experimenting FedML and NVFLARE for Federated Tumor Segmentation Challenge
Multi-stage Deep Layer Aggregation for Brain Tumor Segmentation
Microstructural Modulations in the Hippocampus Allow to Characterizing Relapsing-Remitting Versus Primary Progressive Multiple Sclerosis
Overall Survival Prediction for Glioblastoma on Pre-treatment MRI Using Robust Radiomics and Priors
Federated Learning for Brain Tumor Segmentation Using MRI and Transformers
Multimodal Brain Tumor Classification
Squeeze-and-Excitation Normalization for Brain Tumor Segmentation
TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks
Attention U-Net with Dimension-Hybridized Fast Data Density Functional Theory for Automatic Brain Tumor Image Segmentation
Cascaded Global Context Convolutional Neural Network for Brain Tumor Segmentation
Low-Rank Convolutional Networks for Brain Tumor Segmentation
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part II
Brain Tumor Classification Using 3D Convolutional Neural Network
Ensemble CNN Networks for GBM Tumors Segmentation Using Multi-parametric MRI
Predicting Isocitrate Dehydrogenase Mutation Status in Glioma Using Structural Brain Networks and Graph Neural Networks
Radiogenomic Prediction of MGMT Using Deep Learning with Bayesian Optimized Hyperparameters
Brain Tumor Segmentation with Cascaded Deep Convolutional Neural Network
Utility of Brain Parcellation in Enhancing Brain Tumor Segmentation and Survival Prediction
MRI Brain Tumor Segmentation Using Deep Encoder-Decoder Convolutional Neural Networks
Brain Tumor Segmentation Using Two-Stage Convolutional Neural Network for Federated Evaluation
E 1 D 3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 challenge
BeSt-LeS: Benchmarking Stroke Lesion Segmentation using Deep Supervision
MRI Brain Tumor Segmentation and Uncertainty Estimation Using 3D-UNet Architectures
Unsupervised Anomaly Localization with Structural Feature-Autoencoders
HarDNet-BTS: A Harmonic Shortcut Network for Brain Tumor Segmentation
Automatic Glioma Grading Based on Two-Stage Networks by Integrating Pathology and MRI Images
Feature Learning by Attention and Ensemble with 3D U-Net to Glioma Tumor Segmentation
Coupling nnU-Nets with Expert Knowledge for Accurate Brain Tumor Segmentation from MRI
Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction
DR-Unet104 for Multimodal MRI Brain Tumor Segmentation
A Deep Supervised U-Attention Net for Pixel-Wise Brain Tumor Segmentation
Generalized Wasserstein Dice Loss, Test-Time Augmentation, and Transformers for the BraTS 2021 Challenge
Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings
Multi-view Cross-Modality MR Image Translation for Vestibular Schwannoma and Cochlea Segmentation
An Ensemble of 2D Convolutional Neural Network for 3D Brain Tumor Segmentation
Opportunities and Challenges for Deep Learning in Brain Lesions
Ensemble Outperforms Single Models in Brain Tumor Segmentation
Brain Tumor Segmentation and Survival Prediction
HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation
Deep Learning Based Ensemble Approach for 3D MRI Brain Tumor Segmentation
Probabilistic Tissue Mapping for Tumor Segmentation and Infiltration Detection of Glioma
Cascaded Training Pipeline for 3D Brain Tumor Segmentation
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers, Part II
Bayesian Skip Net: Building on Prior Information for the Prediction and Segmentation of Stroke Lesions
Glioma Segmentation Using Ensemble of 2D/3D U-Nets and Survival Prediction Using Multiple Features Fusion
Model Aggregation for Federated Learning Considering Non-IID and Imbalanced Data Distribution
Brain Tumor Segmentation Using Deep Infomax
Brain Tumor Segmentation Using Neural Ordinary Differential Equations with UNet-Context Encoding Network
Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution
A Review of Medical Federated Learning: Applications in Oncology and Cancer Research
3D U-Net Based Brain Tumor Segmentation and Survival Days Prediction
EfficientNet for Brain-Lesion Classification
Koos Classification of Vestibular Schwannoma via Image Translation-Based Unsupervised Cross-Modality Domain Adaptation
Learning Dynamic Convolutions for Multi-modal 3D MRI Brain Tumor Segmentation
Fully Automated Brain Tumor Segmentation and Survival Prediction of Gliomas Using Deep Learning and MRI
Predicting Clinical Outcome of Stroke Patients with Tractographic Feature
A Hybrid Convolutional Neural Network Based-Method for Brain Tumor Classification Using mMRI and WSI
Primitive Simultaneous Optimization of Similarity Metrics for Image Registration
Brain Tumor Segmentation Network Using Attention-Based Fusion and Spatial Relationship Constraint
Combining Global Information with Topological Prior for Brain Tumor Segmentation
Multimodal Brain Image Segmentation and Analysis with Neuromorphic Attention-Based Learning
Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression
3D MRI Brain Tumor Diagnosis with Topological Descriptors
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I
Brain Tumor Segmentation and Survival Prediction Using 3D Attention UNet
Brain Tumor Segmentation (BraTS) Challenge Short Paper: Improving Three-Dimensional Brain Tumor Segmentation Using SegResnet and Hybrid Boundary-Dice Loss
Federated Learning Using Variable Local Training for Brain Tumor Segmentation
Cascaded Coarse-to-Fine Neural Network for Brain Tumor Segmentation
Transfer Learning for Brain Tumor Segmentation
Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments
Automatic Brain Tumor Segmentation with Scale Attention Network
Evaluating Glioma Growth Predictions as a Forward Ranking Problem
Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation
Efficient Federated Tumor Segmentation via Parameter Distance Weighted Aggregation and Client Pruning
ReFuSeg: Regularized Multi-modal Fusion for Precise Brain Tumour Segmentation
Multi-task Learning for Brain Tumor Segmentation
Two-Step U-Nets for Brain Tumor Segmentation and Random Forest with Radiomics for Survival Time Prediction
Modified MobileNet for Patient Survival Prediction
A Local Score Strategy for Weight Aggregation in Federated Learning
Detection and Segmentation of Brain Tumors from MRI Using U-Nets
Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets
Multi-plane UNet++ Ensemble for Glioblastoma Segmentation
The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview
Robust Image Registration with Absent Correspondences in Pre-operative and Follow-Up Brain MRI Scans of Diffuse Glioma Patients
3D Deep Residual Encoder-Decoder CNNS with Squeeze-and-Excitation for Brain Tumor Segmentation
Extending Probabilistic U-Net Using MC-Dropout to Quantify Data and Model Uncertainty
NnUNet with Region-based Training and Loss Ensembles for Brain Tumor Segmentation
Trialing U-Net Training Modifications for Segmenting Gliomas Using Open Source Deep Learning Framework
Volume Preserving Brain Lesion Segmentation
Improving Brain Tumor Segmentation with Multi-direction Fusion and Fine Class Prediction
Glioma Segmentation with 3D U-Net Backed with Energy-Based Post-Processing
Improved Inter-scanner MS Lesion Segmentation by Adversarial Training on Longitudinal Data
Brain Tumor Segmentation Using Dual-Path Attention U-Net in 3D MRI Images
Temporally Adjustable Longitudinal Fluid-Attenuated Inversion Recovery MRI Estimation / Synthesis for Multiple Sclerosis
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II
3D Inception-Based TransMorph: Pre- and Post-operative Multi-contrast MRI Registration in Brain Tumors
Challenging Current Semi-supervised Anomaly Segmentation Methods for Brain MRI
Prediction of MGMT Methylation Status of Glioblastoma Using Radiomics and Latent Space Shape Features
TBI Lesion Segmentation in Head CT: Impact of Preprocessing and Data Augmentation
Infusing Domain Knowledge into nnU-Nets for Segmenting Brain Tumors in MRI
Optimization with Soft Dice Can Lead to a Volumetric Bias
FedCostWAvg: A New Averaging for Better Federated Learning
Glioma Segmentation Using Encoder-Decoder Network and Survival Prediction Based on Cox Analysis
Robustifying Automatic Assessment of Brain Tumor Progression from MRI
Semi-supervised Variational Autoencoder for Survival Prediction
Residual 3D U-Net with Localization for Brain Tumor Segmentation
Ensemble of CNNs for Segmentation of Glioma Sub-regions with Survival Prediction
3D Brain Tumor Segmentation and Survival Prediction Using Ensembles of Convolutional Neural Networks
Efficient Embedding Network for 3D Brain Tumor Segmentation
Cheap Lunch for Medical Image Segmentation by Fine-Tuning SAM on Few Exemplars
Towards Population-Based Histologic Stain Normalization of Glioblastoma
A Deep Supervision CNN Network for Brain Tumor Segmentation
Optimized U-Net for Brain Tumor Segmentation
Efficient Federated Tumor Segmentation via Normalized Tensor Aggregation and Client Pruning
3D Semantic Segmentation of Brain Tumor for Overall Survival Prediction
Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation
A Video Data Based Transfer Learning Approach for Classification of MGMT Status in Brain Tumor MR Images
Towards Radiomics-Based Automated Disease Progression Assessment for Glioblastoma Patients
Glioma Diagnosis and Classification: Illuminating the Gold Standard
3D MRI Brain Tumour Segmentation with Autoencoder Regularization and Hausdorff Distance Loss Function
Adaptive Weight Aggregation in Federated Learning for Brain Tumor Segmentation
Redundancy Reduction in Semantic Segmentation of 3D Brain Tumor MRIs
Modality-Pairing Learning for Brain Tumor Segmentation
Brain Tumor Segmentation and Associated Uncertainty Evaluation Using Multi-sequences MRI Mixture Data Preprocessing
Brain Tumor Classification Based on MRI Images and Noise Reduced Pathology Images
Multimodal Brain Tumor Segmentation and Survival Prediction Using Hybrid Machine Learning
Assessing Lesion Segmentation Bias of Neural Networks on Motion Corrupted Brain MRI
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans
Employing ConvexAdam for BraTS-Reg
Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images
BRATS2021: Exploring Each Sequence in Multi-modal Input for Baseline U-net Performance
Unsupervised Multimodal Supervoxel Merging Towards Brain Tumor Segmentation
Unsupervised Domain Adaptation for Vestibular Schwannoma and Cochlea Segmentation via Semi-supervised Learning and Label Fusion
Functional Outcome Prediction in Acute Ischemic Stroke
Aggregating Multi-scale Prediction Based on 3D U-Net in Brain Tumor Segmentation
A Joint Graph and Image Convolution Network for Automatic Brain Tumor Segmentation
Brain Tumor Segmentation Using Attention-Based Network in 3D MRI Images
Weakly Unsupervised Domain Adaptation for Vestibular Schwannoma Segmentation
Convolutional 3D to 2D Patch Conversion for Pixel-Wise Glioma Segmentation in MRI Scans
Bag of Tricks for 3D MRI Brain Tumor Segmentation
Deep Convolutional Neural Networks for Brain Tumor Segmentation: Boosting Performance Using Deep Transfer Learning: Preliminary Results
Multi-modal U-Nets with Boundary Loss and Pre-training for Brain Tumor Segmentation
Automatic Classification of Brain Tumor Types with the MRI Scans and Histopathology Images
A Deep Learning Approach to Glioblastoma Radiogenomic Classification Using Brain MRI
Hybrid Labels for Brain Tumor Segmentation
Using Soft Labels to Model Uncertainty in Medical Image Segmentation
Automatic Segmentation of Brain Tumor from 3D MR Images Using SegNet, U-Net, and PSP-Net
Brain Tumor Segmentation in mpMRI Scans (BraTS-2021) Using Models Based on U-Net Architecture
Some New Tricks for Deep Glioma Segmentation
The Tumor Mix-Up in 3D Unet for Glioma Segmentation
Brain Tumor Segmentation with Self-ensembled, Deeply-Supervised 3D U-Net Neural Networks: A BraTS 2020 Challenge Solution
Context Aware 3D UNet for Brain Tumor Segmentation
Automatic Brain Tumor Segmentation with a Bridge-Unet Deeply Supervised Enhanced with Downsampling Pooling Combination, Atrous Spatial Pyramid Pooling, Squeeze-and-Excitation and EvoNorm
Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net
Using Separated Inputs for Multimodal Brain Tumor Segmentation with 3D U-Net-like Architectures
Unsupervised Method for Intra-patient Registration of Brain Magnetic Resonance Images Based on Objective Function Weighting by Inverse Consistency: Contribution to the BraTS-Reg Challenge
Segmentation of the Multimodal Brain Tumor Images Used Res-U-Net
HNF-Netv2 for Brain Tumor Segmentation Using Multi-modal MR Imaging
A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information
Brain Tumour Segmentation Using a Triplanar Ensemble of U-Nets on MR Images
Brain Tumor Segmentation Using UNet-Context Encoding Network
Using Out-of-the-Box Frameworks for Contrastive Unpaired Image Translation for Vestibular Schwannoma and Cochlea Segmentation: An Approach for the CrossMoDA Challenge
Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning
The Detection and Segmentation of Blush in the Lenticulostriate Territory
Quality-Aware Model Ensemble for Brain Tumor Segmentation
Two Stages CNN-Based Segmentation of Gliomas, Uncertainty Quantification and Prediction of Overall Patient Survival
Framework to Generate Perfusion Map from CT and CTA Images in Patients with Acute Ischemic Stroke: A Longitudinal and Cross-Sectional Study
Federated Evaluation of nnU-Nets Enhanced with Domain Knowledge for Brain Tumor Segmentation
An Automatic Overall Survival Time Prediction System for Glioma Brain Tumor Patients Based on Volumetric and Shape Features
Global and Local Multi-scale Feature Fusion Enhancement for Brain Tumor Segmentation and Pancreas Segmentation
Memory-Efficient Cascade 3D U-Net for Brain Tumor Segmentation
2D Dense-UNet: A Clinically Valid Approach to Automated Glioma Segmentation
Multimodal Segmentation with MGF-Net and the Focal Tversky Loss Function
Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for Brain Tumor Segmentation: BraTS 2020 Challenge
Improving Brain Tumor Segmentation in Multi-sequence MR Images Using Cross-Sequence MR Image Generation
An Efficient Cascade of U-Net-Like Convolutional Neural Networks Devoted to Brain Tumor Segmentation
Brain Tumor Segmentation with Self-supervised Enhance Region Post-processing
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation
Segmenting Brain Tumors from MRI Using Cascaded 3D U-Nets
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
MVP U-Net: Multi-View Pointwise U-Net for Brain Tumor Segmentation
MultiATTUNet: Brain Tumor Segmentation and Survival Multitasking
Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients
PieceNet: A Redundant UNet Ensemble
Domain Unlearning Boosts Lesion Segmentation Performance on Seen and Unseen MR Scanner Data
Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty
Multi-resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction
Unsupervised 3D Brain Anomaly Detection
Brain Tumor Segmentation with Patch-Based 3D Attention UNet from Multi-parametric MRI
CNN-Based Fully Automatic Glioma Classification with Multi-modal Medical Images
Tuning U-Net for Brain Tumor Segmentation
Multi-step Cascaded Networks for Brain Tumor Segmentation
Multiple Sclerosis Lesion Segmentation - A Survey of Supervised CNN-Based Methods
Multimodal Brain Tumor Segmentation with Normal Appearance Autoencoder
Brain Tumor Sequence Registration with Non-iterative Coarse-To-Fine Networks and Dual Deep Supervision
Semi-supervised Intracranial Aneurysm Segmentation with Selected Unlabeled Data
Unsupervised Cross-modality Domain Adaptation for Segmenting Vestibular Schwannoma and Cochlea with Data Augmentation and Model Ensemble
Deep Learning for Ischemic Penumbra Segmentation from MR Perfusion Maps: Robustness to the Deconvolution Algorithm
Segmentation, Survival Prediction, and Uncertainty Estimation of Gliomas from Multimodal 3D MRI Using Selective Kernel Networks
A Deep Random Forest Approach for Multimodal Brain Tumor Segmentation
Brain Tumor Segmentation Using Dense Channels 2D U-net and Multiple Feature Extraction Network
Hierarchical and Global Modality Interaction for Brain Tumor Segmentation
Applying Quadratic Penalty Method for Intensity-Based Deformable Image Registration on BraTS-Reg Challenge 2022
Brain Tumor Segmentation from Multiparametric MRI Using a Multi-encoder U-Net Architecture
Diffraction Block in Extended nn-UNet for Brain Tumor Segmentation
Automatic Segmentation of Non-tumor Tissues in Glioma MR Brain Images Using Deformable Registration with Partial Convolutional Networks
MRI Brain Tumor Segmentation Using a 2D-3D U-Net Ensemble
ONCOhabitats Glioma Segmentation Model
Saliency Based Deep Neural Network for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI
Orthogonal-Nets: A Large Ensemble of 2D Neural Networks for 3D Brain Tumor Segmentation
Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation
A Study on Criteria for Training Collaborator Selection in Federated Learning
Multimodal Deep Learning for Functional Outcome Prediction in Endovascular Therapy
Lightweight U-Nets for Brain Tumor Segmentation
Dice Focal Loss with ResNet-like Encoder-Decoder Architecture in 3D Brain Tumor Segmentation
MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation
Multi Modal Fusion for Radiogenomics Classification of Brain Tumor
Towards Learning Geometric Transformations through Play: : An AR-powered approach
A Cloud-Based Mobile Augmented Reality Application for BIM Collaboration
Mixed Reality Guidance System for Motherboard Assembly Using Tangible Augmented Reality
Developing a BIM- and VR-based system to Enhance Layout Modification and Cost Estimation
Virtual Reality For Anatomical Vocabulary Learning
An Evaluation of the Effectiveness of Virtual Reality in Air Traffic Control
Construction and application of virtual simulation training platform for passenger compartment door of urban rail transit
Machining Hole Feature Recognition Method and Application for Manufacturability Check
Guidelines for the Interface Design of AR Systems for Manual Assembly
Influence of Interactive Questions on the Sense of Presence and Anxiety in a Virtual-reality Job-interview Simulation
Research of Cyclone Optimization Based on CFD, GMDH-Type Neural Network and Genetic Algorithm
The 8th International Conference on Virtual and Augmented Reality Simulations, ICVARS 2014, Melbourne, Australia, March 14-16, 2024
ICVARS 2022: The 6th International Conference on Virtual and Augmented Reality Simulations, Brisbane, QLD, Australia, March 25 - 27, 2022
Factors Affecting Acceptance of a Mobile Augmented Reality Application for Cybersecurity Awareness