TransCT: Dual-path Transformer for Low Dose Computed Tomography

Understand

Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radiation to patients.

• However, the noise caused by low X-ray exposure degrades the CT image quality and then affects clinical diagnosis accuracy.
• In this paper, we train a transformer-based neural network to enhance the final CT image quality.
• To be specific, we first decompose the noisy LDCT image into two parts: high-frequency (HF) and low-frequency (LF) compositions.