Rare Congenital Defect Gets a Tech Breakthrough

Situs ambiguus is a condition which is characterised by the abnormal positioning of a patient’s abdominal and thoracic organs. It is associated with an increased risk of numerous health complications.

While tomography such as MRI and CT scans reveal a patient’s internal anatomy, the understanding gained from viewing a three-dimensional object in two dimensions is limited.

Consequently, healthcare teams use diagnostic methods such as colonoscopy which reveal internal anatomy in three dimensions.

In cases of situs ambiguus, the abnormal anatomy renders such diagnostic measures too dangerous to perform, and healthcare teams often turn to invasive surgery to gain a better understanding.

In 2020, Dior Etherton, a Science undergraduate student from Curtin University, was awarded an internship with the university’s Hub for Immersive Visualisation and E-research (the HIVE). With her internship, she studied this rare congenital defect.

Dior’s project, called 3D Reconstruction of Abnormal Viscera focussed on improving the way in which a patient is managing the ongoing symptoms of situs ambiguus, through presenting a better method of visualisation.

This project used a medical imaging software, Analyze 12.0 (AnalyzeDirect, Inc., Lexana, KS, USA), to produce a 3D reconstruction from the CT scans of a patient with situs ambiguus.

The segmentation was developed through a combination of semi-automatic and manual techniques, to yield a 3D object suitable for printing. The object was converted into a stereoscopic video, and a hologram, for presentation on a HoloTable.

This method is an alternative to invasive surgery. It is capable of assisting a healthcare team in patient diagnosis and treatment, which removes the necessity for invasive surgery.

Semi-automatic and manual methods of segmenting tomographic data are time heavy and difficult. To be of use in the medical field, this method needs to be automated.

Dior has recently started working at a medical technology company – Singular Health - which is developing a volumetric rendering software, with this goal of automatic segmentation in mind.

The project will implement machine learning to achieve this automatic segmentation. Various algorithms are being explored, with the goal to have complete segmentation available in a few years.


Dior’s 3D Reconstruction of Abnormal Viscera was a recent winner in the Peter Fillery Undergraduate Student Project of the Year for the 29th Lateral INCITE Awards, showcasing the most outstanding ICT project undertaken by a Western Australia-based tertiary undergraduate student or group of students.

More information on the 3D Reconstruction of Abnormal Viscera can be viewed in Dior's research paper.