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Exploration of Multiscale Geometric Analysis for Enhancement and Structure Detection in MRCP Images

Magnetic Resonance Cholangiopancreatography (MRCP) images are used in the diagnosis and treatment planning of the bile ducts and the liver. The ability to diagnose and treat such diseases in recent times has increased with greater importance placed on the effective use of non-invasive medical imaging. However, MRCP images are often noisy (low signal-to-noise ratio) and suffer from the influence of artifacts, partial volume and large inter-image variations. This paper evaluates the suitability of several Multiscale Geometric Analysis (MGA) techniques, to improve the quality of the 2D MRCP images and enhance the detection of the biliary structures within them. Tests results, evaluated subjectively to correspond with the human visual perception, achieved promising results for contourlets, curvelets as well as a non-orthogonal wavelet noise compensation implementation. The findings may contribute to assist in the development of automatic computer-aided diagnosis systems for liver diseases affecting the bile ducts as well as in clinical diagnosis.