Semi-automatic feature delineation in medical images

Authors:
Robin Martin;Nicole Bordes;Thomas Hugh;Bernard Pailthorpe
Affiliations:
The University of Queensland, Queensland, Australia;The University of Queensland, Queensland, Australia;The University of Sydney, Australia;The University of Queensland, Queensland, Australia
Venue:
APVis '04 Proceedings of the 2004 Australasian symposium on Information Visualisation - Volume 35
Year:
2004

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Abstract

Resection or ablation of tumours is one treatment available for liver cancer. This delicate operation consists of removing the tumour(s) and surrounding healthy tissues. The surgery is complicated by the fact that major blood vessels are present in the liver: the surgeon must proceed cautiously. Computer Tomography (CT) scans are used to diagnose the presence of tumours in the liver but also to assess whether the patient is suitable for surgery. The surgeon needs to find the number of tumours, their size and the physical and spatial relationship between the tumours and the main blood vessels. Extracting this information from the CT scan is a time-consuming procedure, which requires manual contouring of the tumour and the main vessels and is complicated by the low contrast in the images. In this paper we describe a framework, designed within Matlab, to semi-automatically segment the liver, tumours and blood vessels and create a three dimensional (3D) model of the patient's liver suitable for surgery planning.