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Positron Emission Tomography (PET) Images Using Deep Neural Networks

NCT04140565 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 200

Last updated 2019-10-30

No results posted yet for this study

Summary

PET images are based on detecting two annihilation 511 KeV photons that are produced by positron emitting isotopes. The longer the acquisition time, the more photons are detected and processed, resulting in better image quality. However, long scan times (typically 20-40 minutes per scan) are less convenient to patients, and may result in patient motion and misalignment.

several studies have used machine learning to produce diagnostic images from low quality images.The goal of our study is to produce diagnostic PET images with 10 seconds acquisition time per bed position using DNN algorithms

Conditions

  • PET Images and Deep Neural Networks Algorithms

Sponsors & Collaborators

  • Computational Imaging Lab , Dr. Arnaldo Mayer

    collaborator UNKNOWN

  • Sheba Medical Center

    lead OTHER_GOV

Principal Investigators

  • Liran Domachevsky, MD · Sheba Medical Center

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2019-11-01
Primary Completion
2021-11-01
Completion
2021-11-01

Countries

  • Israel

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04140565 on ClinicalTrials.gov