MedTrace Logo

Automated Segmentation and Volumetry for Meningioma Using Deep Learning

NCT05093751 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 600

Last updated 2021-10-26

No results posted yet for this study

Summary

U-Net-based architectures will be applied to 500 contrast-enhanced axial MR images of different patients from a single institution after manual segmentation of meningioma, of which 50 were used for testing. Tumor volumetry after autosegmentation by trained U-Net-based architecture is final goal.

Conditions

  • Meningioma
  • Artificial Intelligence

Interventions

OTHER

Observation

This study does not involve any intervention to subjects.

Sponsors & Collaborators

  • Seoul National University Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2013-03-23
Primary Completion
2021-09-30
Completion
2021-09-30

More Related Trials

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 NCT05093751 on ClinicalTrials.gov