Colonic diverticulitis (CD) is a common entity whose diagnosis is particularly based on computed tomography (CT) examination, which is the imaging technique of choice. However, unusual CT findings of CD may lead to several difficulties and potential pitfalls: due to technical errors in the management of the CT examination, due to the anatomical situation of the diseased colon, in diagnosing unusual complications that may concern the gastrointestinal tract, intra- and retroperitoneal viscera or the abdominal wall, and in differentiating CD from other abdominal inflammatory and infectious conditions or colonic cancer. The aim of this work is to delineate the pitfalls of CT imaging and illustrate misleading CT features in patients with suspected CD.

Abstract. The specification of the nature of the lesion detected is a hard task for chest radiologists. While there are several studies reported in developing a Computer Aided Diagnostic system (CAD), they are limited to the distinction between the cancerous lesions from the non-cancerous. However, physicians need a system which is significantly analogous to a human judgment in the process of analysis and decision making. They need a classifier which can give an idea about the nature of the lesion. This paper presents a comparative analysis between the classification results of the Fuzzy C Means (FCM) and the Support Vector Machines (SVM) algorithms. It discusses also the possibility to increase the interpretability of SVM classifier by its hybridization with the Fuzzy C method.

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