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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 426–450 of 786 papers

TitleStatusHype
Multi-Threshold Attention U-Net (MTAU) based Model for Multimodal Brain Tumor Segmentation in MRI scans—0
Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering—0
Non Parametric Data Augmentations Improve Deep-Learning based Brain Tumor Segmentation—0
ONCOPILOT: A Promptable CT Foundation Model For Solid Tumor Evaluation—0
Optimizing Prediction of MGMT Promoter Methylation from MRI Scans using Adversarial Learning—0
Organ At Risk Segmentation with Multiple Modality—0
PAM-UNet: Shifting Attention on Region of Interest in Medical Images—0
Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models—0
PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Images—0
Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning—0
Parotid Gland MRI Segmentation Based on Swin-Unet and Multimodal Images—0
Partial Labeled Gastric Tumor Segmentation via patch-based Reiterative Learning—0
PCA for Enhanced Cross-Dataset Generalizability in Breast Ultrasound Tumor Segmentation—0
PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training—0
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
PINN-EMFNet: PINN-based and Enhanced Multi-Scale Feature Fusion Network for Breast Ultrasound Images Segmentation—0
Position Paper: Building Trust in Synthetic Data for Clinical AI—0
Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning—0
Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images—0
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning—0
Prediction of Overall Survival of Brain Tumor Patients—0
PriorNet: lesion segmentation in PET-CT including prior tumor appearance information—0
propnet: Propagating 2D Annotation to 3D Segmentation for Gastric Tumors on CT Scans—0
PSO-UNet: Particle Swarm-Optimized U-Net Framework for Precise Multimodal Brain Tumor Segmentation—0
Quantitative Impact of Label Noise on the Quality of Segmentation of Brain Tumors on MRI scans—0
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