AnatomicalNets segments lung structures and computes tumor size and proximity via contours to reach 91.36% T-staging accuracy on Lung-PET-CT-Dx following clinical guidelines.
Imagenet: A large-scale hierarchical image database,
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A decision-aware multi-scale attention network generates tailored explanations for autonomous driving choices and outperforms prior models on F1 and a new Joint F1 metric across two datasets.
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AnatomicalNets: A Multi-Structure Segmentation and Contour-Based Distance Estimation Pipeline for Clinically Grounded Lung Cancer T-Staging
AnatomicalNets segments lung structures and computes tumor size and proximity via contours to reach 91.36% T-staging accuracy on Lung-PET-CT-Dx following clinical guidelines.
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An End-to-End Decision-Aware Multi-Scale Attention-Based Model for Explainable Autonomous Driving
A decision-aware multi-scale attention network generates tailored explanations for autonomous driving choices and outperforms prior models on F1 and a new Joint F1 metric across two datasets.