Precision Identification of Locally Advanced Rectal Cancer in Denoised CT Scans Using EfficientNet and Voting System Algorithms.
Chun-Yu LinJacky Chung-Hao WuYen-Ming KuanYi-Chun LiuPi-Yi ChangJun-Peng ChenHenry Horng-Shing LuOscar Kuang-Sheng LeePublished in: Bioengineering (Basel, Switzerland) (2024)
AI can precisely identify CRM-positive LARC cases from CT images, signaling an increased local recurrence and mortality rate. Our study presents a swifter and more reliable method for detecting LARC compared to traditional CT or MRI techniques.
Keyphrases
- contrast enhanced
- rectal cancer
- dual energy
- locally advanced
- computed tomography
- image quality
- magnetic resonance imaging
- deep learning
- magnetic resonance
- positron emission tomography
- squamous cell carcinoma
- machine learning
- neoadjuvant chemotherapy
- radiation therapy
- diffusion weighted imaging
- artificial intelligence
- cardiovascular events
- phase ii study
- optical coherence tomography
- coronary artery disease
- risk factors
- cardiovascular disease
- study protocol