Neural Network to Calculate Morphology of the Cleft Palate to Reduce Cleft Lip and Palate Treatment Burden.

University Hospital, Basel, Switzerland450 enrolled

Overview

This study is to develop a neural network to compute palatal three dimensional (3D) geometry by using routinely taken intraoral/palatal photographs and palatal casts of infants with cleft lip and palate deformity for reducing cleft lip and palate treatment burden. Data of palatal casts and palatal images of cleft patients routinely treated at the University Hospital Basel will be analyzed.The collection of large data helps in developing a neural network that will allow the computation of the 3D geometry from single photographs.

Study Type

OBSERVATIONAL

Enrollment

450

Conditions

Cleft Palate Orofacial Cleft

Interventions

data collection of palatal casts and palatal images of cleft patients routinely treated at the institutionOTHER

data collection of palatal casts and palatal images of cleft patients, using routinely taken intraoral/palatal photographs and palatal casts of infants with cleft lip and palate deformity

Eligibility

Sex: ALL

Medical Language ↔ Plain English

Inclusion Criteria: * Patients with cleft lip and palate malformation with available routinely performed plaster cast model from palatal impressions, intraoral scans from the palate and corresponding images of the cleft palate (1970 till 2025) Exclusion Criteria: * Existence of a documented rejection

Outcomes

Primary Outcomes

3D palatal geometry

palatal cleft photographs (input) and corresponding 3D palatal geometry (output) create this 3D palatal geometry for development of image based, non-invasive palatal shape reconstruction

Time frame: at baseline

Central Contacts

Benito Benitez, Dr. med. Dr. med. dent.

CONTACT

+41 61 556 52 85 benito.benitez@usb.ch

Andreas Müller, PD Dr. med. Dr. med. dent. Dr.