Study level

  • Vacation research experience scheme

Faculty/School

Faculty of Engineering

School of Mechanical, Medical and Process Engineering

Topic status

We're looking for students to study this topic.

Research centre

Centre for Biomedical Technologies

Supervisors

Associate Professor Paige Little
Position
Principal Research Fellow
Division / Faculty
Faculty of Engineering
Dr Sinduja Suresh
Position
Postdoctoral Research Fellow
Division / Faculty
Faculty of Engineering

External supervisors

  • Dr Geoffrey Askin, QCH
  • Dr Robert Labrom, QCH

Overview

Scoliosis is a three dimensional (3D) spinal deformity that manifests as a structural deformity of the spine and ribcage. Adolescent idiopathic scoliosis (AIS) is the most common presentation, affecting 2-4% of adolescents. AIS has no known cause or cure, and is most frequently severe in females.

Effective management of paediatric scoliosis is heavily reliant upon early diagnosis, and timely specialist appointments at tertiary spine clinics in Brisbane. At these appointments, it is important for the spinal specialist to see the patient's body shape and anatomy, in order to assist with their healthcare planning. But for patients who live in rural Queensland and New South Wales, travel to receive hospital care places financial, temporal and emotional stress on the patient and family, meaning they delay attending much needed healthcare appointments.

We are developing new digital health technology for scoliosis patients who live in rural communities, to ensure they receive equitable access to specialists, without leaving their home. For this purpose we are developing a suite of digital health tools, enabling the remote 'assessment' of patients with scoliosis. One of these tools is 3D surface scanning to capture images of the patient that can be aligned and fused to create a 3D virtual model of the patient's body shape. These images can be captured using the patient's phone and the virtual models can be used by spine specialists at a Children's Hospital to treat the patient.

Research activities

This project will use smart-phones (both Android and iPhones) to capture 2D images of 10-20 AIS patient's torso anatomy.

These 2D images will be aligned and fused using photogrammetric methods, to create a 3D virtual model of the patient's torso.

Images will be captured at different frame rates on each of the devices, and the 3D virtual models compared with 3D models of the same patient created using a high-accuracy non-contact commercial 3D scanner (Artec Eva).

Comparison of the smart-device vs 3D scanner virtual models will be carried out using solid modelling methods, in order to determine the minimum/optimum number of smart-device 2D images that are necessary to achieve an accurate 3D model.

Outcomes

The project outcomes will:

  • determine the optimum number of smart-device captured images that are required to obtain a 3D virtual model of an AIS patient's torso
  • provide a critical analysis of the accuracy of both iPhone and Android phone captured images to create 3D virtual models of patient's torso.

Skills and experience

Some experience with 3D modelling and CAD is desirable, but not essential.

All software and computational methods can be learnt during the course of the project.

You must have an interest and desire to work with 3D simulations and virtual modelling.

Keywords

Contact

Contact the supervisor for more information.