Faculty of Medicine
Faculty of Medicine
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[FG] Facial & Cranial Anomalies

Projects & Collaborations

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Learning-based 3D Infant Face and Head Model for Medical Application

Research Project  | 3 Project Members

Realistic 3D digital models of human heads and faces have the potential to transform current medical practices for pre-treatment diagnostics, treatment planning, patient documentation and quantitative assessment of treatments. In contrast to entertainment where 3D digital faces have become stunningly detailed and realistic with the help of artificial intelligence (AI), medical settings entail several challenges due to the small sizes of real patient data and under-representation of different age groups in the existing datasets.

In this project, we aim at building high-quality models of the human infant face and head learned from real multimodal datasets that derive from the medical treatment of infants. Using these models as priors, we will develop methods to reconstruct individual optimal target morphologies, which can be used as a reference in the treatment planning of infants with craniofacial malformations.

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Burden-Reduced Cleft lip and palate Care and Healing

Research Project  | 3 Project Members

Every 700th birth worldwide is affected by any type of uncompleted development of the upper lip and palatal prominences leading to orofacial cleft (cleft lip and palate). In absence of early surgical correction, main concerns are social discrimination by the disfiguration, nasal leakage of food leading to failure to thrive adequately, and impossibility of speech development. No effective preventive measures exist. Currently, two principles are used and commonly applied complementary as treatment strategies: (1) a palatal plate therapy after birth to keep the tongue out of the cleft space and to narrow the palatal cleft and (2) a multi-step surgical repair. However, this strategy necessitates a palatal impression that endangers the child’s airway and a high surgical burden. The project therefore develops a non-invasive strategy for the palatal plate therapy followed by a one-step surgical repair of the entire cleft lip and palate malformation.

With the use of machine learning algorithms, smartphone-based images of the palate malformation, and 3D printing of tailor-made palatal orthopaedic plates, this project will potentially revolutionise the standard course of treatment of cleft lip and palate. We aim to reduce burden on the patient receiving the cleft lip and palate surgical treatment and to improve the overall long-term outcome. We will exploit our surgical expertise and 3D morphometric knowledges, combined with artificial intelligence to simplify the treatment procedure by developing a ground-breaking new cleft treatment regime:

  1. Image-based, non-invasive palatal shape reconstruction with the aid of smartphones and a software program based on artificial intelligence 
  2. Use of 3D printing (Zarean et al. 2022) following the automated palatal plate design (Schnabel et al. 2023) to simplify the production process
  3. Replace multiple surgical steps with one single surgical intervention through use of the palatal plate (passive plate therapy)

Achieving these goals would provide us with a passive, pre-surgical treatment that is physically, technologically and economically realizable worldwide including in low- and middle-income countries, therefore ultimately enable promotion of single-step surgical treatment to replace the widely performed multi-step surgical treatment which impose large burden on the children and their families.