Polyp enhancing level set evolution of colon wall: method and pilot study.
Computer aided detection (CAD) in computed tomography colonography (CTC) aims at detecting colonic polyps that are the precursors of colon cancer. In this work, we propose a colon wall evolution algorithm polyp enhancing level sets (PELS) based on the level-set formulation that regularizes and enhances polyps as a preprocessing step to CTC CAD algorithms. The underlying idea is to evolve the polyps towards spherical protrusions on the colon wall while keeping other structures, such as haustral folds, relatively unchanged and, thereby, potentially improve the performance of CTC CAD algorithms, especially for smaller polyps. To evaluate our methods, we conducted a pilot study using an arbitrarily chosen CTC CAD method, the surface normal overlap (SNO) CAD algorithm, on a nine patient CTC data set with 47 polyps of sizes ranging from 2.0 to 17.0 mm in diameter. PELS increased the maximum sensitivity by 8.1% (from 21/37 to 24/37) for small polyps of sizes ranging from 5.0 to 9.0 mm in diameter. This is accompanied by a statistically significant separation between small polyps and false positives. PELS did not change the CTC CAD performance significantly for larger polyps.
Konukoglu
Ender
E
Department of Electrical and Electronics Engineering, Boğaziçi University, 34342 Istanbul, Turkey. ender.konukoglu@gmail.com
Acar
Burak
B
Paik
David S
DS
Beaulieu
Christopher F
CF
Rosenberg
Jarrett
J
Napel
Sandy
S
D019412:Anatomy, Cross-Sectional / Q000379:methods; D003106:Colon / Q000000981:diagnostic imaging / Q000473:pathology; D003111:Colonic Polyps / Q000000981:diagnostic imaging* / Q000473:pathology*; D023881:Colonography, Computed Tomographic / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods; D010865:Pilot Projects; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity