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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 276–300 of 786 papers

TitleStatusHype
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation—0
AC-Norm: Effective Tuning for Medical Image Analysis via Affine Collaborative NormalizationCode0
Deepfake Image Generation for Improved Brain Tumor Segmentation—0
Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model—0
Prototype-Driven and Multi-Expert Integrated Multi-Modal MR Brain Tumor Image SegmentationCode1
Confidence Intervals for Performance Estimates in Brain MRI Segmentation—0
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient NetworkCode1
A Novel SLCA-UNet Architecture for Automatic MRI Brain Tumor Segmentation—0
3D Medical Image Segmentation based on multi-scale MPU-NetCode0
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck CancerCode1
Source Identification: A Self-Supervision Task for Dense Prediction—0
The KiTS21 Challenge: Automatic segmentation of kidneys, renal tumors, and renal cysts in corticomedullary-phase CTCode1
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor SegmentationCode1
Feature Imitating Networks Enhance The Performance, Reliability And Speed Of Deep Learning On Biomedical Image Processing TasksCode0
Medical Federated Model with Mixture of Personalized and Sharing ComponentsCode0
AME-CAM: Attentive Multiple-Exit CAM for Weakly Supervised Segmentation on MRI Brain TumorCode1
3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentationCode2
Comparative Analysis of Segment Anything Model and U-Net for Breast Tumor Detection in Ultrasound and Mammography Images—0
M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis TasksCode1
Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging—0
A Novel Confidence Induced Class Activation Mapping for MRI Brain Tumor SegmentationCode0
Computational Modeling of Deep Multiresolution-Fractal Texture and Its Application to Abnormal Brain Tissue Segmentation—0
Volumetric medical image segmentation through dual self-distillation in U-shaped networksCode0
Brain tumor segmentation using synthetic MR images -- A comparison of GANs and diffusion modelsCode1
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI—0
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