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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
M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient SupervisionCode0
A Weakly Supervised and Globally Explainable Learning Framework for Brain Tumor SegmentationCode0
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep LearningCode0
Medical Federated Model with Mixture of Personalized and Sharing ComponentsCode0
MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation NetworkCode0
Multi-modal Evidential Fusion Network for Trustworthy PET/CT Tumor SegmentationCode0
Optimizing Synthetic Data for Enhanced Pancreatic Tumor SegmentationCode0
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image SegmentationCode0
A New Three-stage Curriculum Learning Approach to Deep Network Based Liver Tumor SegmentationCode0
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor SegmentationCode0
Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound DiagnosisCode0
A New Logic For Pediatric Brain Tumor SegmentationCode0
3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor SegmentationCode0
Intensity-Spatial Dual Masked Autoencoder for Multi-Scale Feature Learning in Chest CT SegmentationCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation ProblemsCode0
DSFNet: Dual-GCN and Location-fused Self-attention with Weighted Fast Normalized Fusion for Polyps SegmentationCode0
Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRICode0
Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)Code0
Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing ModalitiesCode0
A Generalized Surface Loss for Reducing the Hausdorff Distance in Medical Imaging SegmentationCode0
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS ChallengeCode0
Distributing Deep Learning Hyperparameter Tuning for 3D Medical Image SegmentationCode0
An attempt at beating the 3D U-NetCode0
Hybrid-Fusion Transformer for Multisequence MRICode0
Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time AugmentationCode0
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor ClassificationCode0
GuideGen: A Text-Guided Framework for Full-torso Anatomy and CT Volume GenerationCode0
Glioblastoma Tumor Segmentation using an Ensemble of Vision TransformersCode0
Glioma Segmentation with Cascaded UnetCode0
H2ASeg: Hierarchical Adaptive Interaction and Weighting Network for Tumor Segmentation in PET/CT ImagesCode0
AutoPET Challenge 2022: Automatic Segmentation of Whole-body Tumor Lesion Based on Deep Learning and FDG PET/CTCode0
Adaptive Active Contour Model for Brain Tumor SegmentationCode0
Generative Style Transfer for MRI Image Segmentation: A Case of Glioma Segmentation in Sub-Saharan AfricaCode0
AutoPET Challenge: Combining nn-Unet with Swin UNETR Augmented by Maximum Intensity Projection ClassifierCode0
Gradient Map-Assisted Head and Neck Tumor Segmentation: A Pre-RT to Mid-RT Approach in MRI-Guided RadiotherapyCode0
Glioblastoma Multiforme Prognosis: MRI Missing Modality Generation, Segmentation and Radiogenomic Survival PredictionCode0
FR-MRInet: A Deep Convolutional Encoder-Decoder for Brain Tumor Segmentation with Relu-RGB and Sliding-windowCode0
FMG-Net and W-Net: Multigrid Inspired Deep Learning Architectures For Medical Imaging SegmentationCode0
Automatic Segmentation of Head and Neck Tumor: How Powerful Transformers Are?Code0
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT VolumesCode0
Domain Knowledge Based Brain Tumor Segmentation and Overall Survival PredictionCode0
Adaptive feature recombination and recalibration for semantic segmentation: application to brain tumor segmentation in MRICode0
Exploiting Partial Common Information Microstructure for Multi-Modal Brain Tumor SegmentationCode0
Automatic Liver Segmentation from CT Images Using Deep Learning Algorithms: A Comparative StudyCode0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
Exploring Feature Representation Learning for Semi-supervised Medical Image SegmentationCode0
Volumetric medical image segmentation through dual self-distillation in U-shaped networksCode0
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing TasksCode0
Evaluation and Analysis of Different Aggregation and Hyperparameter Selection Methods for Federated Brain Tumor SegmentationCode0
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