A paradigm shift in oncology imaging: a prospective cross-sectional study to assess low-dose deep learning image reconstruction versus standard-dose iterative reconstruction for comprehensive lesion detection in dual-energy computed tomography.
Ping HouNana LiuXiangnan FengYan ChenHuixia WangXiaopeng WangJie LiuPengchao ZhanXing LiuBo ShangZhimeng ShenLuotong WangJianbo GaoPeijie LyuPublished in: Quantitative imaging in medicine and surgery (2024)
VMIs at 40 keV with DLIR enables a 50% decrease in the radiation dose while largely maintaining diagnostic capabilities for multidetection of pulmonary nodules, lymph nodes, and liver lesions in oncology patients.
Keyphrases
- dual energy
- computed tomography
- deep learning
- low dose
- image quality
- lymph node
- end stage renal disease
- palliative care
- positron emission tomography
- ejection fraction
- chronic kidney disease
- newly diagnosed
- pulmonary hypertension
- contrast enhanced
- magnetic resonance imaging
- artificial intelligence
- machine learning
- mass spectrometry
- patient reported outcomes
- early stage
- patient reported
- neoadjuvant chemotherapy
- sensitive detection