D.-S. Huang et al. (Eds.): ICIC 2011, LNBI 6840, pp. 596–603, 2012. © Springer-Verlag Berlin Heidelberg 2012 3D Virtual Colonoscopy for Polyps Detection by Supervised Artificial Neural Networks Vitoantonio Bevilacqua 1,2,* , Domenico De Fano 1 , Silvia Giannini 1 , Giuseppe Mastronardi 1,2 , Valerio Paradiso 1 , Marcello Pennini 1 , Michele Piccinni 1 , Giuseppe Angelelli 3 , and Marco Moschetta 3 1 Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari, Bari, Italy 2 e.B.I.S. s.r.l., Politecnico di Bari Spin-Off, Bari, Italy 3 Dipartimento di Medicina Interna e Medicina Pubblica (Di.M.I.M.P.), Sezione di Diagnostica per Immagini, Università degli Studi di Bari, Bari, Italy bevilacqua@poliba.it Abstract. The occurrence of false-positives (FPs) is still an important concern and source of unreliability in computer-aided diagnosis systems developed for 3D virtual colonoscopy. This work presents three different supervised approaches, based on supervised artificial neural networks (ANNs) architectures tested on 16 rows helical multi-slice computer tomography. The performance of the best ANN architecture developed, by using the volumes belonging to only 4 of 7 available nodules diagnosed by expert radiologists as polyps and non-polyps were evaluated in terms of FPs and false-negatives. It revealed good performance in terms of generalization and FPs reduction, correctly detecting all 7 polyps. Keywords: Computer-aided diagnosis, 3D virtual colonoscopy, supervised artificial neural network, colonic polyps detection. 1 Introduction: Materials and Methods The colon and rectal cancers are estimated to be the third carcinoma death cause in western countries. Every year approximately 678.000 new cases are diagnosed in the world and 150.000 in Europe. Although this form of cancer is more curable than other forms of digestive apparatus carcinoma, the possibilities of 5 years surviving from the diagnosis stands at 40-50%, reaching 80-90% in early cases. These statistics show how important is to detect colorectal neoplasia at an early stage in order to ensure the effectiveness of the therapies and reduce the risk of death. Screening programs are, in this perspective, fundamental instruments of diagnosis. Computed tomography colonography (CTC), also known as virtual colonoscopy, is one of the most recent screening test techniques. Although many computer-aided diagnosis (CAD) architectures have been investigated, the occurrence of false-positives (FPs) is still a problem that can lead to less confidence of behalf of technicians in the system and to the eventuality of non-distinction. The aim of this work is to develope a CAD system for CTC that could automatically detect polyps and, in the future, interact with the 3D * Corresponding author.