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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 651–675 of 786 papers

TitleStatusHype
Modified U-Net (mU-Net) with Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images—0
MIScnn: A Framework for Medical Image Segmentation with Convolutional Neural Networks and Deep LearningCode0
Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound ImagesCode0
Organ At Risk Segmentation with Multiple Modality—0
A New Three-stage Curriculum Learning Approach to Deep Network Based Liver Tumor SegmentationCode0
End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation—0
TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks—0
Semi-Supervised Variational Autoencoder for Survival PredictionCode0
Brain MRI Tumor Segmentation with Adversarial Networks—0
Self-supervised Feature Learning for 3D Medical Images by Playing a Rubik's Cube—0
Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes—0
Memory efficient brain tumor segmentation using an autoencoder-regularized U-Net—0
Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans—0
Brain Tumor Segmentation and Survival Prediction—0
Quantitative Impact of Label Noise on the Quality of Segmentation of Brain Tumors on MRI scans—0
3D U-Net Based Brain Tumor Segmentation and Survival Days PredictionCode0
3D Kidneys and Kidney Tumor Semantic Segmentation using Boundary-Aware Networks—0
MRI Brain Tumor Segmentation using Random Forests and Fully Convolutional Networks—0
Prediction of Overall Survival of Brain Tumor Patients—0
Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation—0
Deep Learning for Brain Tumor Segmentation in Radiosurgery: Prospective Clinical Evaluation—0
Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty AnalysisCode1
Kidney tumor segmentation using an ensembling multi-stage deep learning approach. A contribution to the KiTS19 challenge—0
Global Planar Convolutions for improved context aggregation in Brain Tumor Segmentation—0
End-to-End Boundary Aware Networks for Medical Image Segmentation—0
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