Stone detection in MRCP images using controlled region growing
Computers in Biology and Medicine
Reconstruction of biliary structure in 2D MRCP images using multi-scale analysis
Computers in Biology and Medicine
Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis
Computer Methods and Programs in Biomedicine
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We present a preprocessing and segmentation scheme designed to address the particular difficulties encountered in the analysis of magnetic resonance cholangiopancreatography (MRCP) data, as a precursor to the application of computer assisted diagnosis (CAD) techniques. MRCP generates noisy, low resolution, non-isometric data which often exhibits significant greylevel inhomogeneities. This combination of characteristics results in data volumes in which reliable segmentation and analysis are difficult to achieve. In this paper we describe a data processing approach developed to overcome these difficulties and allow for the effective application of automated CAD procedures in the analysis of the biliary tree and pancreatic duct in MRCP examinations.