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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 351–375 of 786 papers

TitleStatusHype
ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentation—0
Exploring 3D U-Net Training Configurations and Post-Processing Strategies for the MICCAI 2023 Kidney and Tumor Segmentation Challenge—0
Segmentation of Kidney Tumors on Non-Contrast CT Images using Protuberance Detection Network—0
T3D: Advancing 3D Medical Vision-Language Pre-training by Learning Multi-View Visual Consistency—0
Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans—0
Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor SegmentationCode0
Seeing Beyond Cancer: Multi-Institutional Validation of Object Localization and 3D Semantic Segmentation using Deep Learning for Breast MRI—0
Automated 3D Tumor Segmentation using Temporal Cubic PatchGAN (TCuP-GAN)—0
Robust Tumor Segmentation with Hyperspectral Imaging and Graph Neural Networks—0
LightBTSeg: A lightweight breast tumor segmentation model using ultrasound images via dual-path joint knowledge distillation—0
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks—0
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point PromptsCode0
Swin UNETR++: Advancing Transformer-Based Dense Dose Prediction Towards Fully Automated Radiation Oncology Treatments—0
Glioblastoma Tumor Segmentation using an Ensemble of Vision TransformersCode0
Hybrid-Fusion Transformer for Multisequence MRICode0
Radiomics as a measure superior to the Dice similarity coefficient for tumor segmentation performance evaluation—0
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation—0
Synthetic Data as Validation—0
Progressive Dual Priori Network for Generalized Breast Tumor SegmentationCode0
MRI brain tumor segmentation using informative feature vectors and kernel dictionary learning—0
Whole-brain radiomics for clustered federated personalization in brain tumor segmentationCode0
RT-SRTS: Angle-Agnostic Real-Time Simultaneous 3D Reconstruction and Tumor Segmentation from Single X-Ray ProjectionCode0
Synthesizing Missing MRI Sequences from Available Modalities using Generative Adversarial Networks in BraTS Dataset—0
Empirical Evaluation of the Segment Anything Model (SAM) for Brain Tumor Segmentation—0
Automated 3D Segmentation of Kidneys and Tumors in MICCAI KiTS 2023 Challenge—0
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