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Development of Three-dimensional Deep Learning for Automatic Design of Skull Implants

NCT05603949 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 6

Last updated 2023-02-13

No results posted yet for this study

Summary

This project aims to develop an effective deep learning system to generate numerical implant geometry based on 3D defective skull models from CT scans. This technique is beneficial for the design of implants to repair skull defects above the Frankfort horizontal plane.

Conditions

  • Skull Defect

Interventions

DEVICE

3D deep learning neural network system

With the consent of the patient, we will assist in the production of images of 3D defect blocks for free (3D deep learning neural network system (3D DNN) system process planning), complete the repair and reconstruction under the clinical routine surgery, and track the repair results after surgery. meet medical needs.

Sponsors & Collaborators

  • Ministry of Science and Technology, Taiwan

    collaborator OTHER_GOV

  • Chang Gung Memorial Hospital

    lead OTHER

Eligibility

Min Age
15 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-02-03
Primary Completion
2023-07-15
Completion
2023-07-15

Countries

  • Taiwan

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 NCT05603949 on ClinicalTrials.gov