Computational Imaging Research Based on Deep Learning

July 21, 2022 updated by: Xin Lou, Chinese PLA General Hospital

Computational Imaging Using Pixel-level Graph Adversarial Learning

Computational imaging research based on deep learning

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

Detailed Description

Based on the current technical challenges, subject development and upgrade of knowledge, to avoid the occurrence of adverse medical accidents, simplify the diagnostic process, artificial intelligence has become the alternative method of choice, by constructing training deep learning model, the CTA as model inputs aneurysm detection and diagnosis to improve diagnosis effectiveness, promote the development of medical technology

Study Type

Observational

Enrollment (Anticipated)

1200

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
      • Beijing, China, 100853
        • Chinese PLA General Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 80 years (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

varity of people

Description

Inclusion Criteria:

  1. Age: 18-80 years.
  2. CT paired imaging data of vessels, including layer-to-layer plain CT and enhanced CT. 2 Time range: January 2010 to December 2021.
  3. Scanning sites: CT and CTA of head, neck, chest, abdomen or iliac.

Exclusion Criteria:

  1. Unpaired CT image .
  2. Severe artifact CT image.
  3. enhancement CT failure image (failure to capture arterial phase or poor arterial development, insufficient flow of contrast agent, etc.)

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Objective evaluation
Time Frame: 30 minutes
using SSIM\MAE index evaluation
30 minutes

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Chinese PLA General Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

November 1, 2021

Primary Completion (ANTICIPATED)

July 30, 2022

Study Completion (ANTICIPATED)

August 15, 2022

Study Registration Dates

First Submitted

July 21, 2022

First Submitted That Met QC Criteria

July 21, 2022

First Posted (ACTUAL)

July 25, 2022

Study Record Updates

Last Update Posted (ACTUAL)

July 25, 2022

Last Update Submitted That Met QC Criteria

July 21, 2022

Last Verified

July 1, 2022

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Synthesis imaging-ChinaPLAGH

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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