Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans

Automatic segmentation of anatomical structures in CT scans is an essential step in the analysis of radiological patient data and is a prerequisite for large-scale content-based image retrieval (CBIR). Many existing segmentation methods are tailored to a single structure and/or require an atlas, which entails multistructure deformable registration and is time-consuming. We present a fully automatic atlas-free segmentation of multiple organs of the ventral cavity in contrast-enhanced CT scans of the whole trunk (CECT). Our method uses a pipeline approach based on the rules that determine the order in which the organs are isolated and how they are segmented. Each organ is individually segmented with a generic four-step procedure. Our method is unique in that it does not require any predefined atlas or a costly registration step and in that it uses the same generic segmentation approach for all organs. Experimental results on the segmentation of seven organs—liver, left and right kidneys, left and right lungs, trachea, and spleen—on 20 CECT scans of the VISCERAL Anatomy training dataset and 10 CECT scans of the test dataset yield an average DICE volume overlap similarity score of 90.95 and 88.50%, respectively.