X Ray
X-ray technology is fundamental to various scientific fields, with current research heavily focused on improving image analysis and interpretation through advanced computational methods. This involves developing and applying deep learning models, including convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), and diffusion models, to automate tasks such as image reconstruction, object detection (e.g., fractures, catheters, lung abnormalities), and report generation. These advancements significantly impact healthcare by enabling faster, more accurate diagnoses and treatment planning, while also enhancing materials science and other fields through improved data analysis and characterization techniques.
Papers
Dual-view X-ray Detection: Can AI Detect Prohibited Items from Dual-view X-ray Images like Humans?
Renshuai Tao, Haoyu Wang, Yuzhe Guo, Hairong Chen, Li Zhang, Xianglong Liu, Yunchao Wei, Yao Zhao
Dual-Level Boost Network for Long-Tail Prohibited Items Detection in X-ray Security Inspection
Renshuai Tao, Haoyu Wang, Wei Wang, Yunchao Wei, Yao Zhao
Comparative Analysis of Machine Learning Approaches for Bone Age Assessment: A Comprehensive Study on Three Distinct Models
Nandavardhan R., Somanathan R., Vikram Suresh, Savaridassan P
DYRECT Computed Tomography: DYnamic Reconstruction of Events on a Continuous Timescale
Wannes Goethals, Tom Bultreys, Steffen Berg, Matthieu N. Boone, Jan Aelterman