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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 601–650 of 786 papers

TitleStatusHype
A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation—0
Efficient embedding network for 3D brain tumor segmentation—0
SoftSeg: Advantages of soft versus binary training for image segmentation—0
Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation—0
Automatic Brain Tumor Segmentation with Scale Attention NetworkCode0
Covariance Self-Attention Dual Path UNet for Rectal Tumor Segmentation—0
Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint—0
Impact of Spherical Coordinates Transformation Pre-processing in Deep Convolution Neural Networks for Brain Tumor Segmentation and Survival Prediction—0
Does anatomical contextual information improve 3D U-Net based brain tumor segmentation?—0
Context Aware 3D UNet for Brain Tumor Segmentation—0
Modality-Pairing Learning for Brain Tumor Segmentation—0
SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation—0
Selective Information Passing for MR/CT Image SegmentationCode0
ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation—0
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network—0
Brain Tumor Segmentation using 3D-CNNs with Uncertainty Estimation—0
Radiologist-level Performance by Using Deep Learning for Segmentation of Breast Cancers on MRI Scans—0
Qutrit-inspired Fully Self-supervised Shallow Quantum Learning Network for Brain Tumor Segmentation—0
Multi-channel MRI Embedding: An EffectiveStrategy for Enhancement of Human Brain WholeTumor SegmentationCode0
Brain Tumor Survival Prediction using Radiomics Features—0
Soft Tissue Sarcoma Co-Segmentation in Combined MRI and PET/CT Data—0
A Cascaded Deep-Learning Framework for Segmentation of Metastatic Brain Tumors Before and After Stereotactic Radiation Therapy—0
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans—0
Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI—0
Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation—0
A Computation-Efficient CNN System for High-Quality Brain Tumor Segmentation—0
E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans—0
Multi-Domain Image Completion for Random Missing Input Data—0
Adaptive feature recombination and recalibration for semantic segmentation with Fully Convolutional NetworksCode0
DSU-net: Dense SegU-net for automatic head-and-neck tumor segmentation in MR images—0
Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet—0
A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction—0
Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation ProblemsCode0
An Inductive Transfer Learning Approach using Cycle-consistent Adversarial Domain Adaptation with Application to Brain Tumor Segmentation—0
Beyond CNNs: Exploiting Further Inherent Symmetries in Medical Images for Segmentation—0
Joint Liver Lesion Segmentation and Classification via Transfer Learning—0
Decentralized Differentially Private Segmentation with PATE—0
Arbitrary Scale Super-Resolution for Brain MRI ImagesCode0
Volumetric Attention for 3D Medical Image Segmentation and Detection—0
Brain tumor segmentation with missing modalities via latent multi-source correlation representation—0
Segmentation of brain tumor on magnetic resonance imaging using a convolutional architecture—0
DDU-Nets: Distributed Dense Model for 3D MRI Brain Tumor Segmentation—0
A Bayesian approach to tissue-fraction estimation for oncological PET segmentation—0
Region of Interest Identification for Brain Tumors in Magnetic Resonance Images—0
Technical report: Kidney tumor segmentation using a 2D U-Net followed by a statistical post-processing filter—0
Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation—0
Brain Tumor Segmentation by Cascaded Deep Neural Networks Using Multiple Image Scales—0
Distributionally Robust Deep Learning using Hardness Weighted SamplingCode0
Transfer Learning for Brain Tumor Segmentation—0
Robustness of Brain Tumor Segmentation—0
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