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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 301–350 of 786 papers

TitleStatusHype
MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation—0
MFA-Net: Multi-Scale feature fusion attention network for liver tumor segmentation—0
Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI—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
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
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
BC-MRI-SEG: A Breast Cancer MRI Tumor Segmentation Benchmark—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
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
Segment anything model for head and neck tumor segmentation with CT, PET and MRI multi-modality imagesCode0
Tumor segmentation on whole slide images: training or prompting?—0
EXACT-Net:EHR-guided lung tumor auto-segmentation for non-small cell lung cancer radiotherapy—0
Re-DiffiNet: Modeling discrepancies in tumor segmentation using diffusion modelsCode0
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor SegmentationCode0
Self-calibrated convolution towards glioma segmentation—0
A Deep Learning Approach for Brain Tumor Classification and Segmentation Using a Multiscale Convolutional Neural Network—0
Disentangled Multimodal Brain MR Image Translation via Transformer-based Modality Infuser—0
Head and Neck Tumor Segmentation from [18F]F-FDG PET/CT Images Based on 3D Diffusion Model—0
CAFCT-Net: A CNN-Transformer Hybrid Network with Contextual and Attentional Feature Fusion for Liver Tumor Segmentation—0
Decentralized Gossip Mutual Learning (GML) for brain tumor segmentation on multi-parametric MRI—0
SEDNet: Shallow Encoder-Decoder Network for Brain Tumor SegmentationCode0
To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detectionCode0
Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain TumorsCode0
Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound DiagnosisCode0
Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet—0
Decentralized Gossip Mutual Learning (GML) for automatic head and neck tumor segmentation—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Using Singular Value Decomposition in a Convolutional Neural Network to Improve Brain Tumor Segmentation Accuracy—0
Integrating Edges into U-Net Models with Explainable Activation Maps for Brain Tumor Segmentation using MR Images—0
Brain Tumor Segmentation Based on Deep Learning, Attention Mechanisms, and Energy-Based Uncertainty PredictionCode0
Multi-task Learning To Improve Semantic Segmentation Of CBCT Scans Using Image Reconstruction—0
Towards SAMBA: Segment Anything Model for Brain Tumor Segmentation in Sub-Sharan African Populations—0
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