A Non-radiation Artificial Intelligence Spine Deformity Diagnosis System
Grant Data
Project Title
A Non-radiation Artificial Intelligence Spine Deformity Diagnosis System
Principal Investigator
Dr Cheung, Jason Pui Yin
(Principal Investigator (PI))
Duration
11
Start Date
2022-05-26
Amount
372863
Conference Title
A Non-radiation Artificial Intelligence Spine Deformity Diagnosis System
Keywords
Non-radiation, Artificial Intelligence, Spine Deformity Diagnosis System
Discipline
Regenerative Medicine
HKU Project Code
PiH/175/22
Grant Type
Research Talent Hub for ITF Projects (RTH-ITF)
Funding Year
2023
Status
On-going
Objectives
Spinal deformity is prevalent in adolescents (3%) and elderly (60%). Back pain is aleading global cause of disability and a large percentage is contributed to deformity.Without proper intervention, the disease can progress rapidly, thus close follow-up of thepatients is critical. However, this is associated with an enormous economic burden on thepublic healthcare system.The first line of medical imaging is X-ray for diagnosing and assessment of spinedeformities. Clinical decisions are based mainly on the alignment parameters like Cobbangles and lumbar lordosis measured by specialists on X-rays. Repetitive X-rays arerequired at nearly every routine follow-up to guide timely interventions. Repeated X-raysare associated with high radiation exposure which increases the risk of cancer. Thus, theavailability of an easily accessible and non-radiation system that also objectivelyassesses the deformity of the patients is crucial.In this project, we will develop a portable and low-cost radiation-free AI-powered systemfor spine deformity diagnosis using depth-sensing technology. Specifically, we will (1)establish a large dataset using depth camera with paired X-ray images labelled byspecialists, (2) design and implement different AI-integrated pipelines for spinal deformityseverity grading, and (3) clinically validate the developed system.