Development and validation of a self-attention network-based algorithm to detect mediastinal lesions on computed tomography images.
Sizhu WuShengyu LiuMing ZhongErik R de LoosMarc HartertÁlvaro Fuentes-MartínAlessandra LenziniDejian WangQing QianPublished in: Journal of thoracic disease (2024)
The proposed model showed excellent performance in detecting mediastinal lesions on CT. Thus, it can drastically reduce radiologists' workload, improve their performance, and speed up the reporting time in everyday clinical practice.
Keyphrases
- computed tomography
- lymph node
- clinical practice
- deep learning
- dual energy
- positron emission tomography
- image quality
- contrast enhanced
- ultrasound guided
- artificial intelligence
- machine learning
- magnetic resonance imaging
- working memory
- convolutional neural network
- optical coherence tomography
- emergency department