AI of cleft lip images to create an automated appearance outcome score

  • Research type

    Research Study

  • Full title

    Using artificial intelligence to develop a software tool for automatic measurement of facial appearance outcome for children with a repaired complete unilateral cleft lip (Deep Score Net).

  • IRAS ID

    324262

  • Contact name

    Bruce Richard

  • Contact email

    bruce.richard@nhs.net

  • Sponsor organisation

    Birmingham Women and Children's Hospital NHS Trust

  • Clinicaltrials.gov Identifier

    8546, Research registry UIN

  • Duration of Study in the UK

    2 years, 0 months, 1 days

  • Research summary

    Parents of children born with a cleft lip want to have confidence that their cleft team will do the best technical operation according to the best protocol to get the best outcome in terms of facial appearance. We know how to measure other important outcomes in cleft, such as psychological, speech, dental and facial growth, in a robust scientific way, yet we are unable to measure facial appearance. This project will use artificial intelligence to score facial photographs of children with a cleft lip, repaired in the first 6 months of life by an operation and assessed from a facial photograph at age five years. The scores will be correlated directly to scores made by groups of humans to ensure that they are meaningful. Our aim is to create an easy-to-use automated software tool that can score how a person’s face looks after cleft lip surgery, which will enable cleft teams to assess which technical method, timing or surgeon gets the best result.
    The project is funded by a grant from Cleft - Bridging the gap, a UK research charity.

  • REC name

    Yorkshire & The Humber - South Yorkshire Research Ethics Committee

  • REC reference

    23/YH/0037

  • Date of REC Opinion

    9 Mar 2023

  • REC opinion

    Further Information Favourable Opinion