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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 151–175 of 786 papers

TitleStatusHype
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor SegmentationCode1
Hybrid Window Attention Based Transformer Architecture for Brain Tumor SegmentationCode1
CSC-PA: Cross-image Semantic Correlation via Prototype Attentions for Single-network Semi-supervised Breast Tumor SegmentationCode1
Knowledge Distillation for Brain Tumor SegmentationCode1
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
DeepSeg: Deep Neural Network Framework for Automatic Brain Tumor Segmentation using Magnetic Resonance FLAIR ImagesCode1
Esophageal Tumor Segmentation in CT Images using Dilated Dense Attention Unet (DDAUnet)Code1
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient NetworkCode1
Medical Image Segmentation Using Squeeze-and-Expansion TransformersCode1
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text CuesCode1
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck CancerCode1
mlf-core: a framework for deterministic machine learningCode1
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation—0
A Modality-Adaptive Method for Segmenting Brain Tumors and Organs-at-Risk in Radiation Therapy Planning—0
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint—0
Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks—0
Automated Tumor Segmentation and Brain Mapping for the Tumor Area—0
Automated Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy from DWI Data—0
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention—0
AMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation—0
Automated head and neck tumor segmentation from 3D PET/CT—0
Automated ensemble method for pediatric brain tumor segmentation—0
A Cascaded Deep-Learning Framework for Segmentation of Metastatic Brain Tumors Before and After Stereotactic Radiation Therapy—0
Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities—0
Automated Ensemble-Based Segmentation of Adult Brain Tumors: A Novel Approach Using the BraTS AFRICA Challenge Data—0
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