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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 626–650 of 786 papers

TitleStatusHype
Multi-Domain Image Completion for Random Missing Input Data—0
Multi-encoder nnU-Net outperforms Transformer models with self-supervised pretraining—0
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation—0
Multi-Layer Feature Fusion with Cross-Channel Attention-Based U-Net for Kidney Tumor Segmentation—0
Multimodal 3D Brain Tumor Segmentation with Adversarial Training and Conditional Random Field—0
Multi-modal Brain Tumor Segmentation via Missing Modality Synthesis and Modality-level Attention Fusion—0
Multi-Modal Brain Tumor Segmentation via 3D Multi-Scale Self-attention and Cross-attention—0
Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRICode0
Co-Learning Feature Fusion Maps from PET-CT Images of Lung CancerCode0
Patient-Specific Real-Time Segmentation in Trackerless Brain UltrasoundCode0
Sine Wave Normalization for Deep Learning-Based Tumor Segmentation in CT/PET ImagingCode0
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural NetworksCode0
Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO)Code0
Intensity-Spatial Dual Masked Autoencoder for Multi-Scale Feature Learning in Chest CT SegmentationCode0
Category Guided Attention Network for Brain Tumor Segmentation in MRICode0
Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time AugmentationCode0
Automatic Brain Tumor Segmentation with Scale Attention NetworkCode0
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss functionCode0
A New Three-stage Curriculum Learning Approach to Deep Network Based Liver Tumor SegmentationCode0
A New Logic For Pediatric Brain Tumor SegmentationCode0
Post-hoc Overall Survival Time Prediction from Brain MRICode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS ChallengeCode0
A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete ModalitiesCode0
Automatic Brain Tumor Segmentation using Cascaded Anisotropic Convolutional Neural NetworksCode0
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