## 1 Introduction  
Colorectal cancer is the second leading cause of cancer related death in western countries and the third most common human malignancy in the United States [1]. Most colorectal cancers arise from pre-malignant polyps in the colon that develop into cancer over time. The progression from polyp to cancerous lesion takes more than ten years for most patients. Because of this slow growth rate, colon cancer screening [2] is an effective method for polyp detection, and subsequent removal reduces the riskof colorectal cancer by up to 90 percent [3]. Colonoscopy, the endoscopic examination of the colon using a flexible video camera, is the standard approach to colorectal screening; however, in recent years there has been much interest in CT Colonography (CTC), which uses CT images of the cleansed and insufflated colon [4]. Polyps can then be detected by a clinical reader who examines the CT data using advanced visualization software that provides both 3D endoluminal views of the colon as well as 2D multi-planar reformatted slices.  
Compared to optical colonoscopy, CTC has the advantages that it affords rapid imaging of the entire colon, is less invasive, and has virtually no risk of perforation of the colon. Clinical studies suggest CTC can provide similar detection performance as colonoscopy but has a reduced risk of complication [5]. Although CT imaging typically exposes the patient to 5-8 mSv of radiation, this exposure is comparable to a few years of natural background radiation, and therefore should not be a significant component of the consideration to use CTC for polyp screening [6].  
The lesion size is directly related to the likelihood of malignancy [2]. Diminutive polyps, _i.e._, those less than 6 mm in size (measured in the single largest dimension of the polyp head) are not thought to confer significant clinical risk. Small polyps in the 6-9 mm range are typically pre-cancerous and are of interest for reporting during the exam; such polyps may be flagged for surveillance or surgical removal. Lesions 10 mm and larger confer higher clinical risk, as 10-25% of these lesions may exhibit malignancy.  
Although CTC has been demonstrated to be an effective colorectal screening approach [7], it is possible for the clinical reader to fail to detect lesions, due to the large quantity of data generated (typically 800-2000 images per patient). Computer-aided detection (CAD) software assists the clinical reader by automatically analyzing the CT data and highlighting potential lesions. CAD may detect lesions that would have otherwise been missed by the reader, and furthermore may give the reader more confidence that lesions were not missed during the read. It has been demonstrated that the use of CAD leads to improvements in reader performance (at all levels of experience) in detecting lesions in CTC data [8; 9].  
An important challenge in developing CAD software is robustness, as the CAD must work effectively across a wide range of operating conditions. Patients may have different preparations, including the type and degree of cathartic cleansing, the use or lack thereof of liquid and fecal tagging agents, and level of insufflation of the colon during scanning. Different imaging hardware (from various manufacturers) or imaging protocols (slice thickness, tube current, patient positioning, _etc._) may be employed. Populations may have differences as well, coming from different institutions, and may be symptomatic or asymptomatic. Another, often overlooked issue relates to the computational resources required to run the CAD. Given the vast quantity of data to be analyzed, the processing must be fast in order to optimize the clinical workflow, and additionally be memory efficient to be practical when running in conjunction with advanced visualization software.