Automated liver segmentation using a normalized probabilistic atlas

Probabilistic atlases of anatomical organs, especially the brain and the heart, have become popular in medical image analysis. We propose the construction of probabilistic atlases which retain structural variability by using a size-preserving modified affine registration. The organ positions are modeled in the physical space by normalizing the physical organ locations to an anatomical landmark. In this paper, a liver probabilistic atlas is constructed and exploited to automatically segment liver volumes from abdominal CT data. The atlas is aligned with the patient data through a succession of affine and non-linear registrations. The overlap and correlation with manual segmentations are 0.91 (0.93 DICE coefficient) and 0.99 respectively. Little work has taken place on the integration of volumetric measures of liver abnormality to clinical evaluations, which rely on linear estimates of liver height. Our application measures the liver height at the mid-hepatic line (0.94 correlation with manual measurements) and indicates that its combination with volumetric estimates could assist the development of a noninvasive tool to assess hepatomegaly.

[1]  Hans-Peter Meinzer,et al.  A Shape-Guided Deformable Model with Evolutionary Algorithm Initialization for 3D Soft Tissue Segmentation , 2007, IPMI.

[2]  S. Sletting,et al.  The volume of the liver in patients correlates to body weight and alcohol consumption. , 2000, Alcohol and alcoholism.

[3]  Nikos Paragios,et al.  Liver Segmentation Using Sparse 3D Prior Models with Optimal Data Support , 2007, IPMI.

[4]  Ronald M. Summers,et al.  Multi-organ automatic segmentation in 4D contrast-enhanced abdominal CT , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[5]  Hervé Delingette,et al.  Towards a Statistical Atlas of Cardiac Fiber Structure , 2006, MICCAI.

[6]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Thomas Lange,et al.  Shape Constrained Automatic Segmentation of the Liver based on a Heuristic Intensity Model , 2007 .

[8]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[10]  Colin Studholme,et al.  An overlap invariant entropy measure of 3D medical image alignment , 1999, Pattern Recognit..

[11]  K. Sandrasegaran,et al.  Measurement of liver volume using spiral CT and the curved line and cubic spline algorithms: reproducibility and interobserver variation , 1999, Abdominal Imaging.

[12]  Benoit M. Dawant,et al.  Semi-automatic Segmentation of the Liver and its Evaluation on the MICCAI 2007 Grand Challenge Data Set , 2007 .

[13]  Hyunjin Park,et al.  Construction of an abdominal probabilistic atlas and its application in segmentation , 2003, IEEE Transactions on Medical Imaging.

[14]  B. Ginneken,et al.  3D Segmentation in the Clinic: A Grand Challenge , 2007 .

[15]  Maria Athelogou,et al.  Cognition Network Technology for a Fully Automated 3D Segmentation of Liver , 2007 .

[16]  S. Casciaro,et al.  A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans , 2008, European Radiology.

[17]  Volker Aurich,et al.  HepaTux - A Semiautomatic Liver Segmentation System , 2007 .

[18]  L. Ruskó,et al.  Fully automatic liver segmentation for contrast-enhanced CT images , 2007 .

[19]  A. Sonnenberg,et al.  Liver size evaluated by ultrasound: ROC curves for hepatitis and alcoholism. , 1984, Radiology.

[20]  Daniel Rueckert,et al.  Segmentation of 4D Cardiac MR Images Using a Probabilistic Atlas and the EM Algorithm , 2003, MICCAI.

[21]  Guido Gerig,et al.  Unbiased diffeomorphic atlas construction for computational anatomy , 2004, NeuroImage.

[22]  R. Woods,et al.  Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain , 2000, Human brain mapping.

[23]  B. Gosink,et al.  Ultrasonic determination of hepatomegaly , 1981, Journal of clinical ultrasound : JCU.

[24]  D F Leotta,et al.  Estimation of the human liver volume and configuration using three-dimensional ultrasonography: effect of a high-caloric liquid meal. , 1998, Ultrasound in medicine & biology.

[25]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.