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Tumor Segmentation

Tumor Segmentation is the task of identifying the spatial location of a tumor. It is a pixel-level prediction where each pixel is classified as a tumor or background. The most popular benchmark for this task is the BraTS dataset. The models are typically evaluated with the Dice Score metric.

Papers

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Showing 251–300 of 786 papers

TitleStatusHype
Decentralized Differentially Private Segmentation with PATE—0
Decentralized Gossip Mutual Learning (GML) for automatic head and neck tumor segmentation—0
Decentralized Gossip Mutual Learning (GML) for brain tumor segmentation on multi-parametric MRI—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet—0
Glioblastoma Multiforme Patient Survival Prediction—0
A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction—0
Artificial Intelligence Solution for Effective Treatment Planning for Glioblastoma Patients—0
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation—0
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans—0
Brain Tumor Survival Prediction using Radiomics Features—0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
A Review on Automated Brain Tumor Detection and Segmentation from MRI of Brain—0
AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation—0
Brain Tumor Segmentation Using Deep Learning by Type Specific Sorting of Images—0
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features—0
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks—0
Brain Tumor Segmentation using 3D-CNNs with Uncertainty Estimation—0
Brain Tumor Segmentation on MRI with Missing Modalities—0
A Prior Knowledge Based Tumor and Tumoral Subregion Segmentation Tool for Pediatric Brain Tumors—0
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training—0
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint—0
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer—0
A Pretrained DenseNet Encoder for Brain Tumor Segmentation—0
Brain Tumor Segmentation from MRI Images using Deep Learning Techniques—0
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
A Performance-Consistent and Computation-Efficient CNN System for High-Quality Automated Brain Tumor Segmentation—0
A deep learning model integrating FCNNs and CRFs for brain tumor segmentation—0
2D-Densely Connected Convolution Neural Networks for automatic Liver and Tumor Segmentation—0
Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation—0
A Novel SLCA-UNet Architecture for Automatic MRI Brain Tumor Segmentation—0
Experimenting with Knowledge Distillation techniques for performing Brain Tumor Segmentation—0
A Novel Method for Automatic Segmentation of Brain Tumors in MRI Images—0
Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma—0
Exploring 3D U-Net Training Configurations and Post-Processing Strategies for the MICCAI 2023 Kidney and Tumor Segmentation Challenge—0
Brain Tumor Segmentation and Survival Prediction using Automatic Hard mining in 3D CNN Architecture—0
Generative Adversarial Networks for Weakly Supervised Generation and Evaluation of Brain Tumor Segmentations on MR Images—0
Brain Tumor Segmentation and Survival Prediction—0
A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network—0
Exploring Adult Glioma through MRI: A Review of Publicly Available Datasets to Guide Efficient Image Analysis—0
Brain Tumor Segmentation: A Comparative Analysis—0
AdaViT: Adaptive Vision Transformer for Flexible Pretrain and Finetune with Variable 3D Medical Image Modalities—0
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation—0
Brain Tumor Detection Based On Symmetry Information—0
Brain Tumor Detection Based On Mathematical Analysis and Symmetry Information—0
Anisotropic Hybrid Networks for liver tumor segmentation with uncertainty quantification—0
3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context—0
Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation—0
Brain MRI study for glioma segmentation using convolutional neural networks and original post-processing techniques with low computational demand—0
Targeted Neural Architectures in Multi-Objective Frameworks for Complete Glioma Characterization from Multimodal MRI—0
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