Improving low-dose lung CT imaging using advanced algorithms

Nonlinear performance analysis and prediction for robust low dose lung CT

['FUNDING_R01'] · UNIVERSITY OF PENNSYLVANIA · NIH-10755743

This study is looking at new ways to make low-dose lung CT scans clearer and more accurate, so patients can get better diagnoses and monitoring of their lung health while being exposed to less radiation.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF PENNSYLVANIA (nih funded)
Locations1 site (PHILADELPHIA, UNITED STATES)
Trial IDNIH-10755743 on ClinicalTrials.gov

What this research studies

This research focuses on enhancing the quality of low-dose lung CT scans through the use of nonlinear algorithms, such as model-based reconstruction and deep learning techniques. By analyzing and predicting the performance of these advanced imaging methods, the study aims to improve the accuracy and reliability of lung imaging while minimizing radiation exposure. The approach involves systematic evaluation of various imaging parameters and their impact on image quality, ensuring that the algorithms can be effectively applied in clinical settings. Patients may benefit from more accurate diagnoses and better monitoring of lung conditions with reduced radiation risks.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals requiring lung imaging, particularly those at risk for lung diseases.

Not a fit: Patients who do not require lung imaging or have conditions that do not involve lung assessment may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to safer and more effective lung imaging techniques for patients.

How similar studies have performed: Previous research has shown promise in using nonlinear algorithms for imaging, indicating potential for success in this novel approach.

Where this research is happening

PHILADELPHIA, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.