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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 651–700 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
Squeeze Excitation Embedded Attention UNet for Brain Tumor Segmentation—0
A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation—0
Stratify or Inject: Two Simple Training Strategies to Improve Brain Tumor Segmentation—0
Variational U-Net with Local Alignment for Joint Tumor Extraction and Registration (VALOR-Net) of Breast MRI Data Acquired at Two Different Field Strengths—0
Deep Superpixel Generation and Clustering for Weakly Supervised Segmentation of Brain Tumors in MR Images—0
SurgicalVLM-Agent: Towards an Interactive AI Co-Pilot for Pituitary Surgery—0
3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context—0
VIViT: Variable-Input Vision Transformer Framework for 3D MR Image Segmentation—0
SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images—0
Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatments—0
Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology—0
Combining CNN and Hybrid Active Contours for Head and Neck Tumor Segmentation in CT and PET images—0
Combining CNNs With Transformer for Multimodal 3D MRI Brain Tumor Segmentation With Self-Supervised Pretraining—0
Comparative Analysis of Image Enhancement Techniques for Brain Tumor Segmentation: Contrast, Histogram, and Hybrid Approaches—0
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation—0
Comparative Analysis of Segment Anything Model and U-Net for Breast Tumor Detection in Ultrasound and Mammography Images—0
Comparison of machine learning methods for classifying mediastinal lymph node metastasis of non-small cell lung cancer from 18F-FDG PET/CT images—0
Clinical Inspired MRI Lesion Segmentation—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Computational Modeling of Deep Multiresolution-Fractal Texture and Its Application to Abnormal Brain Tissue Segmentation—0
Class Balanced PixelNet for Neurological Image Segmentation—0
Conditional generator and multi-sourcecorrelation guided brain tumor segmentation with missing MR modalities—0
Confidence Intervals for Performance Estimates in Brain MRI Segmentation—0
Conquering Data Variations in Resolution: A Slice-Aware Multi-Branch Decoder Network—0
Context Aware 3D UNet for Brain Tumor Segmentation—0
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