Improving imaging techniques for human extremities using advanced computer algorithms

Unsupervised Deep Photon-Counting Computed Tomography Reconstruction for Human Extremity Imaging

['FUNDING_R01'] · UNIVERSITY OF MASSACHUSETTS LOWELL · NIH-11090461

This study is working on using smart computer technology to make CT scans of arms and legs clearer and safer, so patients can get better pictures of their tissues without as much radiation.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF MASSACHUSETTS LOWELL (nih funded)
Locations1 site (LOWELL, UNITED STATES)
Trial IDNIH-11090461 on ClinicalTrials.gov

What this research studies

This research focuses on enhancing computed tomography (CT) imaging for human extremities by utilizing advanced deep learning algorithms. The approach aims to improve image quality while reducing radiation exposure, making it safer for patients. By leveraging big data, the study seeks to train a deep learning network that can reconstruct high-quality images from x-ray photon-counting CT scans. This could lead to better tissue characterization and more accurate diagnoses.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals requiring imaging of their extremities, such as those with injuries or conditions affecting bones and soft tissues.

Not a fit: Patients who do not require imaging of their extremities or those with conditions that do not involve the use of CT imaging may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could provide patients with safer and more accurate imaging techniques for diagnosing conditions affecting their extremities.

How similar studies have performed: Other research has shown promise in using deep learning for image reconstruction, indicating that this approach could lead to significant advancements in imaging technology.

Where this research is happening

LOWELL, 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.