ECR 2026 | Ultra-High Resolution Deep Learning Reconstruction in Chest CT Imaging
New deep learning reconstruction (DLR) techniques are transforming CT imaging by enabling ultra-high-resolution images. When applied to chest CT, DLR significantly enhances image quality through noise reduction and improved spatial resolution, all without increasing radiation dose. This advancement allows clearer visualization of fine pulmonary, vascular, and airway structures, improving detection and characterization of subtle lung lesions and interstitial abnormalities. However, important questions remain: How reliable are these images? Can we fully trust what we see, and what is the impact on clinical decision-making? Finally, how can such technologies be effectively integrated into routine imaging practice?
Workshop recording from ECR 2026
Prof. Stefan M. Niehues
Radiologist
Caritas Clinics, Berlin, GermanyCourse Information
At the end of this lecture, delegates will:
- Learn how PIQE 1024 enhances your thoracic CT imaging
- Gain trust into next-gen thoracic imaging
This educational talk was created on 6th March 2026. All information contained in this session was correct at the time of distribution.
Disclaimer: Appearing on the Canon Medical Academy does not represent a commercial partnership or interest from the speaker. The views herein do not represent the views of Canon Medical Systems Ltd.
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