SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–400 of 786 papers

TitleStatusHype
FedGraph: an Aggregation Method from Graph Perspective—0
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation—0
FedPID: An Aggregation Method for Federated Learning—0
FedPIDAvg: A PID controller inspired aggregation method for Federated Learning—0
Few-Shot Generation of Brain Tumors for Secure and Fair Data Sharing—0
Brain Tumor Segmentation and Survival Prediction using Automatic Hard mining in 3D CNN Architecture—0
Flexible Fusion Network for Multi-modal Brain Tumor Segmentation—0
AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients—0
Focus, Segment and Erase: An Efficient Network for Multi-Label Brain Tumor Segmentation—0
Free-form Lesion Synthesis Using a Partial Convolution Generative Adversarial Network for Enhanced Deep Learning Liver Tumor Segmentation—0
Brain Tumor Segmentation and Survival Prediction—0
The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI—0
Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors—0
Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet—0
Fully Automatic Brain Tumor Segmentation using a Normalized Gaussian Bayesian Classifier and 3D Fluid Vector Flow—0
GANet-Seg: Adversarial Learning for Brain Tumor Segmentation with Hybrid Generative Models—0
Brain Tumor Segmentation: A Comparative Analysis—0
Brain Tumor Detection Based On Symmetry Information—0
Brain Tumor Detection Based On Mathematical Analysis and Symmetry Information—0
Generating 3D Brain Tumor Regions in MRI using Vector-Quantization Generative Adversarial Networks—0
Brain Tumor Classification by Cascaded Multiscale Multitask Learning Framework Based on Feature Aggregation—0
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma—0
Glioblastoma Multiforme Patient Survival Prediction—0
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)—0
A Hybrid Framework for Tumor Saliency Estimation—0
Glioma Multimodal MRI Analysis System for Tumor Layered Diagnosis via Multi-task Semi-supervised Learning—0
A Feasibility study for Deep learning based automated brain tumor segmentation using Magnetic Resonance Images—0
Global Planar Convolutions for improved context aggregation in Brain Tumor Segmentation—0
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa)—0
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI—0
The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)—0
H2NF-Net for Brain Tumor Segmentation using Multimodal MR Imaging: 2nd Place Solution to BraTS Challenge 2020 Segmentation Task—0
HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging—0
Brain MRI study for glioma segmentation using convolutional neural networks and original post-processing techniques with low computational demand—0
AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation—0
Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model—0
3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures—0
Here Comes the Explanation: A Shapley Perspective on Multi-contrast Medical Image Segmentation—0
Hierarchical Convolutional-Deconvolutional Neural Networks for Automatic Liver and Tumor Segmentation—0
Hierarchical Fine-Tuning for joint Liver Lesion Segmentation and Lesion Classification in CT—0
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function—0
End-to-End Boundary Aware Networks for Medical Image Segmentation—0
HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation—0
HNF-Netv2 for Brain Tumor Segmentation using multi-modal MR Imaging—0
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation—0
Hybrid Attention Network for Accurate Breast Tumor Segmentation in Ultrasound Images—0
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks—0
Hybridization of Attention UNet with Repeated Atrous Spatial Pyramid Pooling for Improved Brain Tumour Segmentation—0
Hybrid Multihead Attentive Unet-3D for Brain Tumor Segmentation—0
Show:102550
← PrevPage 8 of 16Next →

No leaderboard results yet.