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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 651–675 of 786 papers

TitleStatusHype
Self-supervised Tumor Segmentation through Layer Decomposition—0
Semantic Feature Attention Network for Liver Tumor Segmentation in Large-scale CT database—0
Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learning—0
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation—0
2D-Densely Connected Convolution Neural Networks for automatic Liver and Tumor Segmentation—0
An attempt at beating the 3D U-Net—0
Using Singular Value Decomposition in a Convolutional Neural Network to Improve Brain Tumor Segmentation Accuracy—0
Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model—0
Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images—0
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities—0
An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI—0
Slice-by-slice deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for spatial uncertainty on FDG PET and CT images—0
Slice Imputation: Intermediate Slice Interpolation for Anisotropic 3D Medical Image Segmentation—0
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation—0
Analyzing Deep Learning Based Brain Tumor Segmentation with Missing MRI Modalities—0
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI—0
DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling—0
SoftSeg: Advantages of soft versus binary training for image segmentation—0
Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data—0
Source Identification: A Self-Supervision Task for Dense Prediction—0
Spatially Covariant Lesion Segmentation—0
Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decomposition—0
Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI—0
Split-U-Net: Preventing Data Leakage in Split Learning for Collaborative Multi-Modal Brain Tumor Segmentation—0
A Multi-View Dynamic Fusion Framework: How to Improve the Multimodal Brain Tumor Segmentation from Multi-Views?—0
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