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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 151–200 of 786 papers

TitleStatusHype
BrainSegFounder: Towards 3D Foundation Models for Neuroimage SegmentationCode1
Enhancing Incomplete Multi-modal Brain Tumor Segmentation with Intra-modal Asymmetry and Inter-modal DependencyCode0
Evaluating the Impact of Sequence Combinations on Breast Tumor Segmentation in Multiparametric MRI—0
Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learning—0
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor SegmentationCode1
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce RegimesCode1
The ULS23 Challenge: a Baseline Model and Benchmark Dataset for 3D Universal Lesion Segmentation in Computed TomographyCode1
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models—0
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation—0
Dealing with All-stage Missing Modality: Towards A Universal Model with Robust Reconstruction and Personalization—0
FreeTumor: Advance Tumor Segmentation via Large-Scale Tumor SynthesisCode2
MGI: Multimodal Contrastive pre-training of Genomic and Medical Imaging—0
Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation—0
The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI—0
SiNGR: Brain Tumor Segmentation via Signed Normalized Geodesic Transform RegressionCode1
Hybrid Multihead Attentive Unet-3D for Brain Tumor Segmentation—0
Patient-Specific Real-Time Segmentation in Trackerless Brain UltrasoundCode0
Self-supervised learning improves robustness of deep learning lung tumor segmentation to CT imaging differences—0
Meta-Learned Modality-Weighted Knowledge Distillation for Robust Multi-Modal Learning with Missing DataCode0
MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation—0
Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI—0
MFA-Net: Multi-Scale feature fusion attention network for liver tumor segmentation—0
On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural NetworksCode0
PAM-UNet: Shifting Attention on Region of Interest in Medical Images—0
MiM: Mask in Mask Self-Supervised Pre-Training for 3D Medical Image Analysis—0
PRISM: A Promptable and Robust Interactive Segmentation Model with Visual PromptsCode1
The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)—0
A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete ModalitiesCode0
BC-MRI-SEG: A Breast Cancer MRI Tumor Segmentation Benchmark—0
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor ClassificationCode0
LATUP-Net: A Lightweight 3D Attention U-Net with Parallel Convolutions for Brain Tumor Segmentation—0
Comparative Analysis of Image Enhancement Techniques for Brain Tumor Segmentation: Contrast, Histogram, and Hybrid Approaches—0
Automated Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy from DWI Data—0
Deep Learning-Based Brain Image Segmentation for Automated Tumour Detection—0
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation—0
H2ASeg: Hierarchical Adaptive Interaction and Weighting Network for Tumor Segmentation in PET/CT ImagesCode0
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 ChallengeCode0
Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets—0
Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection—0
Federated Modality-specific Encoders and Multimodal Anchors for Personalized Brain Tumor SegmentationCode1
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor SegmentationCode0
Advanced Tumor Segmentation in Medical Imaging: An Ensemble Approach for BraTS 2023 Adult Glioma and Pediatric Tumor Tasks—0
DALSA: Domain Adaptation for Supervised Learning From Sparsely Annotated MR Images—0
BraSyn 2023 challenge: Missing MRI synthesis and the effect of different learning objectives—0
GuideGen: A Text-Guided Framework for Full-torso Anatomy and CT Volume GenerationCode0
A Segmentation Foundation Model for Diverse-type Tumors—0
Modality-Aware and Shift Mixer for Multi-modal Brain Tumor Segmentation—0
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