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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

Showing 151200 of 786 papers

TitleStatusHype
DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasetsCode1
Memory-Efficient 3D Denoising Diffusion Models for Medical Image ProcessingCode1
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentationCode1
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation TaskCode1
DR-Unet104 for Multimodal MRI brain tumor segmentationCode1
Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple HospitalsCode1
Self Pre-training with Masked Autoencoders for Medical Image Classification and SegmentationCode1
Weakly supervised multiple instance learning histopathological tumor segmentationCode1
Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRICode1
Fed-MUnet: Multi-modal Federated Unet for Brain Tumor SegmentationCode1
A Multimodal Feature Distillation with CNN-Transformer Network for Brain Tumor Segmentation with Incomplete ModalitiesCode0
Automatic brain tumor segmentation in 2D intra-operative ultrasound images using MRI tumor annotationsCode0
MRI Tumor Segmentation with Densely Connected 3D CNNCode0
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance ImagingCode0
MSTT-199: MRI Dataset for Musculoskeletal Soft Tissue Tumor SegmentationCode0
3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic VolumesCode0
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep LearningCode0
Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma SegmentationCode0
Multi-channel MRI Embedding: An EffectiveStrategy for Enhancement of Human Brain WholeTumor SegmentationCode0
A Localization-to-Segmentation Framework for Automatic Tumor Segmentation in Whole-Body PET/CT ImagesCode0
3D Medical Image Segmentation based on multi-scale MPU-NetCode0
Autofocus Layer for Semantic SegmentationCode0
Medical Federated Model with Mixture of Personalized and Sharing ComponentsCode0
MAProtoNet: A Multi-scale Attentive Interpretable Prototypical Part Network for 3D Magnetic Resonance Imaging Brain Tumor ClassificationCode0
MBDRes-U-Net: Multi-Scale Lightweight Brain Tumor Segmentation NetworkCode0
M-GenSeg: Domain Adaptation For Target Modality Tumor Segmentation With Annotation-Efficient SupervisionCode0
Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound ImagesCode0
Attention-Enhanced Hybrid Feature Aggregation Network for 3D Brain Tumor SegmentationCode0
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image SegmentationCode0
A transformer-based deep learning approach for classifying brain metastases into primary organ sites using clinical whole brain MRICode0
A4-Unet: Deformable Multi-Scale Attention Network for Brain Tumor SegmentationCode0
SmoothSegNet: A Global-Local Framework for Liver Tumor Segmentation with Clinical KnowledgeInformed Label SmoothingCode0
A Study on the Performance of U-Net Modifications in Retroperitoneal Tumor SegmentationCode0
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss functionCode0
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor SegmentationCode0
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithmCode0
UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor SegmentationCode0
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ SegmentationCode0
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point PromptsCode0
AGD-Autoencoder: Attention Gated Deep Convolutional Autoencoder for Brain Tumor SegmentationCode0
Iterative Semi-Supervised Learning for Abdominal Organs and Tumor SegmentationCode0
A fuzzy rank-based ensemble of CNN models for MRI segmentationCode0
Breast Tumor Segmentation and Shape Classification in Mammograms using Generative Adversarial and Convolutional Neural NetworkCode0
Intensity-Spatial Dual Masked Autoencoder for Multi-Scale Feature Learning in Chest CT SegmentationCode0
Improved automated lesion segmentation in whole-body FDG/PET-CT via Test-Time AugmentationCode0
3D-TransUNet for Brain Metastases Segmentation in the BraTS2023 ChallengeCode0
Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRICode0
3D Dilated Multi-Fiber Network for Real-time Brain Tumor Segmentation in MRICode0
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