Multi-organ automatic segmentation in 4D contrast-enhanced abdominal CT

Abstract

Medical imaging and computer-aided diagnosis (CAD) traditionally focus on organ- or disease-based applications. To shift from organ-based to organism-based approaches, CAD needs to replicate the work of radiologists and analyze consecutively multiple organs. A fully automatic method is presented for the simultaneous segmentation of four abdominal organs from 4D CT data. Abdominal contrast- enhanced CT scans from sixteen patients were obtained at three phases: non-contrast, arterial and portal. Intra- patient data is registered non-rigidly using the demons algorithm and smoothed with anisotropic diffusion. Mutual information accounts for intensity variability within the same organ during subsequent acquisitions and data are interpolated with cubic B-splines. Then heterogeneous erosion is applied to multi-phase data using the intensity characteristics of the liver, spleen, and kidneys. The erosion filter is a 4D convolution that preserves only image regions that satisfy the above intensity criteria. Finally, a geodesic level set completes the segmentation of the four abdominal organs. This 3D evaluation of abdominal data shows great promise as a computer-aided radiology tool for multi-organ and multi-disease analysis.