Pixel Wised Lesion Prediction on COVID-19 CT Imagery: A Comparative Analysis of Automated Image Segmentation Architectures

arXiv:2605.20459 · cs.CV, cs.AI · Submitted 2026-05-19 · Read on arXiv

cs.CV, cs.AI

Submitted: 2026-05-19

Updated: 2026-08-27

Terminology

• Accuracy — 9× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Feature Pyramid Network — 2× in this paper
• Loss Function — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Annotation Errors — 1× in this paper · explained in 1 episode
• Visual Geometry Group — 1× in this paper

Sources

• Automated Chest CT Image Segmentation of COVID-19 Lung Infection based on 3D U-Net
• MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation
• Very Deep Convolutional Networks for Large-Scale Image Recognition
• MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

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