Improving initial polyp candidate extraction for CT colonography.

Reducing the number of false positives (FPs) as much as possible is a challenging task for computer-aided detection (CAD) of colonic polyps. As part of a typical CAD pipeline, an accurate and robust process for segmenting initial polyp candidates (IPCs) will significantly benefit the successive FP reduction procedures, such as feature-based classification of false and true positives (TPs). In this study, we introduce an improved scheme for segmenting IPCs. It consists of two main components. One is geodesic distance-based merging, which merges suspicious patches (SPs) for IPCs. Based on the merged SPs, another component, called convex dilation, grows each SP beyond the inner surface of the colon wall to form a volume of interest (VOI) for that IPC, so that the inner border of the VOI beyond the colon inner surface could be segmented as convex, as expected. The IPC segmentation strategy was evaluated using a database of 50 patient studies, which include 100 scans at supine and prone positions with 84 polyps and masses sized from 6 to 35 mm. The presented IPC segmentation strategy (or VOI extraction method) demonstrated improvements, in terms of having no undesirably merged true polyp and providing more helpful mean and variance of the image intensities rooted from the extracted VOI for classification of the TPs and FPs, over two other VOI extraction methods (i.e. the conventional method of Nappi and Yoshida (2003 Med. Phys. 30 1592-601) and our previous method (Zhu et al 2009 Cancer Manag. Res. 1 1-13). At a by-polyp sensitivity of 0.90, these three methods generated the FP rate (number of FPs per scan) of 4.78 (new method), 6.37 (Nappi) and 7.01 (Zhu) respectively.