Computer-aided detection of colonic polyps using low-dose CT acquisitions.

Rationale and Objectives: This report proposes an alternative method for the automatic detection of colonic polyps that is robust enough to be directly applicable on low-dose computed tomographic data.
Materials and Methods: The polyp modeling process takes into account both the gray-level appearance of polyps (intensity profiles) and their geometry (extended Gaussian images). Spherical harmonic decompositions are used for comparison purposes, allowing fast estimation of the similarity between a candidate and a set of previously computed models. Starting from the original raw data (acquired at 55 mA), five patient data sets (prone and supine scans) are reconstructed at different dose levels (to 5 mA) by using different kernel filters, slice overlaps, and increments. Additionally, the efficacy of applying an edge-preserving smoothing filter before detection is assessed.
Results: Although image quality decreases when decreasing acquisition milliamperes, all polyps greater than 6 mm are detected successfully, even at 15 mA. Although not important at high doses, smoothing improves detection results for ultra-low-dose (tube current<15 mA) data.
Conclusion: The advantage of low-dose scans is a significant decrease in effective dose from 4.93 to 1.61 mSv while retaining high detection values, particularly important when thinking of population screening.