Robustness Studies Of Ultrasound Cadx In Breast Cancer Diagnosis

This chapter will focus on the robustness, or reliability, of computer-aided diagnosis, abbreviated as CADx. In CADx, computerized analysis is used to characterize abnormalities identified by a human user (e.g., a radiologist). CADx is part of the broader area of imaging (Giger Chan, & Boone, 2008). Other examples of quantitative imaging applications include computer-aided detection (Drukker et al., 2002; Drukker, Giger & Mendelson, 2003), computer-aided prognosis (Bhooshan, et al., 2010), and computer-aided assessment of response to therapy (Shi, et al., 2009; S'hiraishi, Li, Appelbaum, Pu, & Doi, 2007). The task of primary interest in this chapter is the diagnosis of breast cancer using sonographic images(i.e., the distinction between benign and malignant breast lesions). The only steps that require human interaction are the identification of suspicious abnormalities prior to the computerized analysis by the CADx system and the interpretation of the CADx results. It is important to note that CADx only provides the radiologist with additional information. The,final decision as to whether or not a given abnormality is worrisome lies with the radiologist. In order ilbr CADx to be of potential help it is required that a CADx system demonstrates not only good but also consistent perfbrmance. The latter aspect is the focus of this chapter in which the authors will explore causes of variability and investigate CADx performance under different realistic scenarios.