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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 551–575 of 786 papers

TitleStatusHype
United adversarial learning for liver tumor segmentation and detection of multi-modality non-contrast MRI—0
SAR: Scale-Aware Restoration Learning for 3D Tumor Segmentation—0
Unpaired cross-modality educed distillation (CMEDL) for medical image segmentation—0
Unsupervised Brain Tumor Segmentation with Image-based Prompts—0
Unveiling Incomplete Modality Brain Tumor Segmentation: Leveraging Masked Predicted Auto-Encoder and Divergence Learning—0
Using Singular Value Decomposition in a Convolutional Neural Network to Improve Brain Tumor Segmentation Accuracy—0
Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images—0
Variational U-Net with Local Alignment for Joint Tumor Extraction and Registration (VALOR-Net) of Breast MRI Data Acquired at Two Different Field Strengths—0
VIViT: Variable-Input Vision Transformer Framework for 3D MR Image Segmentation—0
Volumetric Attention for 3D Medical Image Segmentation and Detection—0
Weakly supervised pan-cancer segmentation tool—0
Deep segmentation networks predict survival of non-small cell lung cancer—0
When SAM Meets Medical Images: An Investigation of Segment Anything Model (SAM) on Multi-phase Liver Tumor Segmentation—0
Whole-body tumor segmentation of 18F -FDG PET/CT using a cascaded and ensembled convolutional neural networks—0
Within-Brain Classification for Brain Tumor Segmentation—0
Incomplete Multi-modal Brain Tumor Segmentation via Learnable Sorting State Space Model—0
Incremental Learning for Heterogeneous Structure Segmentation in Brain Tumor MRI—0
Integrating cross-modality hallucinated MRI with CT to aid mediastinal lung tumor segmentation—0
Integrating Edges into U-Net Models with Explainable Activation Maps for Brain Tumor Segmentation using MR Images—0
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Intraoperative Glioma Segmentation with YOLO + SAM for Improved Accuracy in Tumor Resection—0
Investigating certain choices of CNN configurations for brain lesion segmentation—0
Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation—0
ISA-Net: Improved spatial attention network for PET-CT tumor segmentation—0
Is Long Range Sequential Modeling Necessary For Colorectal Tumor Segmentation?—0
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