Graph-Cut Energy Minimization for Object Extraction in MRCP Medical Images

Bile duct identification and extraction in magnetic resonance cholangiopancreatography (MRCP) images, is a necessary step in the development of computer-aided diagnosis systems using such images. MRCP is becoming the de facto modality in the diagnosis of biliary diseases and even in the pre-surgical workup for liver transplants. The energy minimization graph-cut method is a proven technique in the extraction of objects in natural images, and even used in 3D reconstruction. This paper proposes several versions of the graph-cut approach for the extraction of the biliary structures in MRCP images. The schemes include a fully interactive lazy snapping method, a manual point selection method for minimal user interaction and an automated phase unwrapping via max flows (PUMA) implementation. The performance of the algorithms vary, but the results support that the scheme is a promising semi-automated object extraction scheme for the significant biliary structures in medical MRCP images.

[1]  Rajasvaran Logeswaran,et al.  Neural networks aided stone detection in thick slab MRCP images , 2006, Medical and Biological Engineering and Computing.

[2]  Andrew Zisserman,et al.  OBJ CUT , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[3]  Robert Pless,et al.  Interactive Separation of Segmented Bones in CT Volumes Using Graph Cut , 2008, MICCAI.

[4]  Mark Hedley,et al.  A new two‐dimensional phase unwrapping algorithm for MRI images , 1992, Magnetic resonance in medicine.

[5]  José M. Bioucas-Dias,et al.  Phase Unwrapping via Graph Cuts , 2005, IEEE Transactions on Image Processing.

[6]  Baozong Yuan,et al.  Better Foreground Segmentation for Static Cameras via New Energy Form and Dynamic Graph-cut , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[7]  Keechul Jung,et al.  Better Foreground Segmentation for 3D Face Reconstruction Using Graph Cuts , 2007, PSIVT.

[8]  Rajasvaran Logeswaran,et al.  A Computer-aided Multidisease Diagnostic System Using MRCP , 2008, Journal of Digital Imaging.

[9]  Harry Shum,et al.  Lazy snapping , 2004, ACM Trans. Graph..

[10]  Eric V. Denardo,et al.  Flows in Networks , 2011 .

[11]  Rajasvaran Logeswaran,et al.  Liver Isolation in Abdominal MRI , 2008, Journal of Medical Systems.

[12]  P. Wayne Power,et al.  Understanding Background Mixture Models for Foreground Segmentation , 2002 .

[13]  Marie-Pierre Jolly,et al.  Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[14]  J. Dillenseger,et al.  Graph Cut Liver Segmentation for Interstitial Ultrasound Therapy , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[15]  Leo Grady,et al.  Random Walks for Image Segmentation , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[16]  S. Casciaro,et al.  Fully Automatic Liver Segmentation through Graph-Cut Technique , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[17]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Gareth Funka-Lea,et al.  Automatic heart isolation for CT coronary visualization using graph-cuts , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[19]  Loris Nanni,et al.  Local Ternary Patterns from Three Orthogonal Planes for human action classification , 2011, Expert Syst. Appl..

[20]  Leo Grady,et al.  A Seeded Image Segmentation Framework Unifying Graph Cuts And Random Walker Which Yields A New Algorithm , 2007, 2007 IEEE 11th International Conference on Computer Vision.