title: Computer-aided detection for CT colonography: update 2007.
abstract: Computed tomographic colonography (CTC) is an emerging technique for polyp detection in the colon. However, lesion detection can be challenging due to insufficient patient preparation, chosen CT technique or reader imperfection. The primary goal of computer-aided detection (CAD) for CTC is locating possible polyps, and presenting the reader with these polyp candidates. Other goals are sensitivity improvement and reduction of reading time and inter-observer variability. The multistep CAD procedure typically consists of segmentation of the colonic wall (e.g. region growing); selection of intermediate polyp candidates (curvature analysis, sphere fitting, normal analysis, slope density function ...); classification of final candidates for detection and listing suspicious polyps (location, size and volume). Remaining task for the radiologist is the validation or rejection of the polyp candidates. State-of-the-art CAD systems should require minimal or even no user interaction for the extraction of the colonic wall, offer a computation time less than 10-20 min and high sensitivity and specificity for different polyp sizes and shapes, with a low number of false positives. These systems have the potential to increase radiologist's performance and to decrease inter-reader variability. Besides CAD key techniques we also discuss new developments in CAD and describe recent applications facilitating CTC.
authors: Department of Radiology, University Hospital Gasthuisberg KU Leuven, Herestraat 49, 3000 Leuven, Belgium. didier.bielen@uz.kuleuven.ac.be
authors: Didier
authors: D
authors: Bielen
authors: Gabriel
authors: G
authors: Kiss
mesh_terms: D001331:Automation; D003110:Colonic Neoplasms / Q000175:diagnosis*; D003111:Colonic Polyps / Q000175:diagnosis; D023881:Colonography, Computed Tomographic / Q000379:methods* / Q000639:trends; D003936:Diagnosis, Computer-Assisted / Q000379:methods* / Q000639:trends; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity