title: Shape filtering for false positive reduction at computed tomography colonography.
abstract: In this paper, we treat the problem of reducing the false positives (FP) in the automatic detection of colorectal polyps at Computer Aided Detection in Computed Tomography Colonography (CAD-CTC) as a shape-filtering task. From the extracted candidate surface, we obtain a reliable shape distribution function and analyse it in the Fourier domain and use the resulting spectral data to classify the candidate surface as belonging to a polyp or a non-polyp class. The developed shape filtering scheme is computationally efficient (takes approximately 2 seconds per dataset to detect the polyps from the colonic surface) and offers robust polyp detection with an overall false positive rate of 5.44 per dataset at a sensitivity of 100% for polyps greater than 10 mm when it was applied to standard and low dose CT data.
authors.affiliation: Vision Systems Group, Dublin City University, Ireland. abhilash@eeng.dcu.ie
authors.forename: Abhilash A
authors.initials: AA
authors.lastname: Miranda
authors.forename: Tarik A
authors.initials: TA
authors.lastname: Chowdhury
authors.forename: Ovidiu
authors.initials: O
authors.lastname: Ghita
authors.forename: Paul F
authors.initials: PF
authors.lastname: Whelan
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D003111:Colonic Polyps / Q000000981:diagnostic imaging*; D023881:Colonography, Computed Tomographic / Q000379:methods*; D005189:False Positive Reactions; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity