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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 201–250 of 786 papers

TitleStatusHype
Category Guided Attention Network for Brain Tumor Segmentation in MRICode0
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithmCode0
UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor SegmentationCode0
M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient SupervisionCode0
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ SegmentationCode0
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep LearningCode0
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point PromptsCode0
AGD-Autoencoder: Attention Gated Deep Convolutional Autoencoder for Brain Tumor SegmentationCode0
SmoothSegNet: A Global-Local Framework for Liver Tumor Segmentation with Clinical KnowledgeInformed Label SmoothingCode0
Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma SegmentationCode0
Medical Federated Model with Mixture of Personalized and Sharing ComponentsCode0
Multi-channel MRI Embedding: An EffectiveStrategy for Enhancement of Human Brain WholeTumor SegmentationCode0
MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation NetworkCode0
A fuzzy rank-based ensemble of CNN models for MRI segmentationCode0
Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural NetworkCode0
Co-Learning Feature Fusion Maps from PET-CT Images of Lung CancerCode0
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor SegmentationCode0
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 ChallengeCode0
3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRICode0
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor ClassificationCode0
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance ImagingCode0
Regularized Weight Aggregation in Networked Federated Learning for Glioblastoma SegmentationCode0
3D U-Net Based Brain Tumor Segmentation and Survival Days PredictionCode0
Brain tumour segmentation using a triplanar ensemble of U-NetsCode0
Brain Tumor Segmentation using Enhanced U-Net Model with Empirical AnalysisCode0
Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)Code0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Intensity-Spatial Dual Masked Autoencoder for Multi-Scale Feature Learning in Chest CT SegmentationCode0
Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time AugmentationCode0
One-pass Multi-task Networks with Cross-task Guided Attention for Brain Tumor SegmentationCode0
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS ChallengeCode0
Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRICode0
Hybrid-Fusion Transformer for Multisequence MRICode0
Optimizing Synthetic Data for Enhanced Pancreatic Tumor SegmentationCode0
H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT VolumesCode0
Cross-Modality Brain Tumor Segmentation via Bidirectional Global-to-Local Unsupervised Domain AdaptationCode0
3D Medical Image Segmentation based on multi-scale MPU-NetCode0
3D-DDA: 3D Dual-Domain Attention for Brain Tumor SegmentationCode0
Head and Neck Tumor Segmentation of MRI from Pre- and Mid-radiotherapy with Pre-training, Data Augmentation and Dual Flow UNetCode0
Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing ModalitiesCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image SegmentationCode0
Glioma Segmentation with Cascaded UnetCode0
Brain Tumor Segmentation Based on Refined Fully Convolutional Neural Networks with A Hierarchical Dice LossCode0
Gradient Map-Assisted Head and Neck Tumor Segmentation: A Pre-RT to Mid-RT Approach in MRI-Guided RadiotherapyCode0
Brain Tumor Segmentation Based on Deep Learning, Attention Mechanisms, and Energy-Based Uncertainty PredictionCode0
Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival PredictionCode0
GuideGen: A Text-Guided Framework for Full-torso Anatomy and CT Volume GenerationCode0
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Glioblastoma Multiforme Prognosis: MRI Missing Modality Generation, Segmentation and Radiogenomic Survival PredictionCode0
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