Development of Three-dimensional Deep Learning for Automatic Design of Skull Implants
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Designing a personalized implant to restore the protective and aesthetic functions of the patient's skull is challenging. The skull defects may be caused by trauma, congenital malformation, infection, and iatrogenic treatments such as decompressive craniectomy, plastic surgery, and tumor resection. The project aims to develop a deep learning system with 3D shape reconstruction capabilities. The system will meet the requirement of designing high-resolution 3D implant numerical models efficiently.
A collection of skull images were used for training the deep learning system. Defective models in the datasets were created by numerically masking areas of intact 3D skull models. The final implant design should be verified by neurosurgeons using 3D printed models.
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Yau-zen chang
- Phone Number: 5341 (03)211-8800
- Email: zen@mail.cgu.edu.tw
Study Locations
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-
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Taoyuan City, Taiwan, 333
- Recruiting
- Linkou Chang Gung Memorial Hospital
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Contact:
- Yau-zen Chang, PhD
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- Scheduled for cranioplasty
- Informed consent
Exclusion Criteria:
(1)No informed consent
Study Plan
How is the study designed?
Design Details
- Observational Models: Case-Only
- Time Perspectives: Retrospective
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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experimental group
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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.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Number of patients where there is no need to adapt the Patient Specific Implant (PSI) edges
Time Frame: 6 weeks after surgery by standardised questionnaire
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Number of patients where there is no need to adapt the Patient Specific Implant (PSI) edges
|
6 weeks after surgery by standardised questionnaire
|
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Number of patients where there is no need to augment/fill clefts between the Patient Specific Implant (PSI) and patient´s bone
Time Frame: 6 weeks after surgery by standardised questionnaire
|
Number of patients where there is no need to augment/fill clefts between the Patient Specific Implant (PSI) and patient´s bone
|
6 weeks after surgery by standardised questionnaire
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (ACTUAL)
Study Start
Primary Completion (ANTICIPATED)
Primary Completion
Study Completion (ANTICIPATED)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (ACTUAL)
First Posted
Study Record Updates
Last Update Posted (ACTUAL)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 202201082B0
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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