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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
Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated FusionCode1
Knowledge Distillation for Brain Tumor SegmentationCode1
Stan: Small tumor-aware network for breast ultrasound image segmentationCode1
Robust Semantic Segmentation of Brain Tumor Regions from 3D MRIsCode1
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and AnalysisCode1
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 ChallengeCode1
Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty AnalysisCode1
The Liver Tumor Segmentation Benchmark (LiTS)Code1
Lesion Focused Super-ResolutionCode1
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 ChallengeCode1
BUSIS: A Benchmark for Breast Ultrasound Image SegmentationCode1
Brain Tumor Segmentation with Deep Neural NetworksCode1
HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging—0
GANet-Seg: Adversarial Learning for Brain Tumor Segmentation with Hybrid Generative Models—0
Hybrid Attention Network for Accurate Breast Tumor Segmentation in Ultrasound Images—0
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention—0
BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet—0
Enhancing Privacy: The Utility of Stand-Alone Synthetic CT and MRI for Tumor and Bone Segmentation—0
DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling—0
Efficient 3D Brain Tumor Segmentation with Axial-Coronal-Sagittal EmbeddingCode0
PCA for Enhanced Cross-Dataset Generalizability in Breast Ultrasound Tumor Segmentation—0
Hypergraph Tversky-Aware Domain Incremental Learning for Brain Tumor Segmentation with Missing ModalitiesCode0
TAGS: 3D Tumor-Adaptive Guidance for SAM—0
VIViT: Variable-Input Vision Transformer Framework for 3D MR Image Segmentation—0
UPMAD-Net: A Brain Tumor Segmentation Network with Uncertainty Guidance and Adaptive Multimodal Feature FusionCode0
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