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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 126–150 of 786 papers

TitleStatusHype
Exploring Adult Glioma through MRI: A Review of Publicly Available Datasets to Guide Efficient Image Analysis—0
Intraoperative Glioma Segmentation with YOLO + SAM for Improved Accuracy in Tumor Resection—0
Anatomical Consistency Distillation and Inconsistency Synthesis for Brain Tumor Segmentation with Missing Modalities—0
Detection of Under-represented Samples Using Dynamic Batch Training for Brain Tumor Segmentation from MR Images—0
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment—0
Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor SegmentationCode0
Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRICode1
A Weakly Supervised and Globally Explainable Learning Framework for Brain Tumor SegmentationCode0
UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor SegmentationCode0
Optimizing Synthetic Data for Enhanced Pancreatic Tumor SegmentationCode0
CBCTLiTS: A Synthetic, Paired CBCT/CT Dataset For Segmentation And Style Transfer—0
Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIsCode0
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023—0
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer—0
MBA-Net: SAM-driven Bidirectional Aggregation Network for Ovarian Tumor Segmentation—0
Embracing Massive Medical DataCode1
AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients—0
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text CuesCode1
RobU-Net: a heuristic robust multi-class brain tumor segmentation approaches for MRI scans—0
Multi-modal Evidential Fusion Network for Trustworthy PET/CT Tumor SegmentationCode0
Unsupervised Domain Adaptation for Pediatric Brain Tumor SegmentationCode1
CAVM: Conditional Autoregressive Vision Model for Contrast-Enhanced Brain Tumor MRI SynthesisCode1
CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset—0
Multimodal Learning With Intraoperative CBCT & Variably Aligned Preoperative CT Data To Improve Segmentation—0
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes—0
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