SCALE-SPACE SEGMENT GROWING FOR HIERARCHICAL DETECTION OF BILIARY TREE STRUCTURE
Abstract
Liver diseases are a common medical problem, especially amongst the population of developing countries. Magnetic Resonance Cholangio Pancreatography (MRCP) has become the popular non-invasive, non-ionizing examination for analysis of the hepatobiliary structure in the liver. Unfortunately, conventional 2D MRCP images can be difficult to analyze for biliary tree anomalies, especially with volume effect, artefacts and noise present in these images, whilst good 3D MRI systems are costly for less affluent nations. This paper proposes a scale-space multi-resolution approach to a segment-based implementation of the popular region growing algorithm, to identify the hierarchical structure of the biliary tree in conventional 2D MRCP images. Results obtained are promising in aiding automatic processing of these images to assist medical practitioners in analyzing the biliary tract more efficiently. Application of the algorithm may be extended for telemedicine.
