title: Application of artificial neural networks in computer-aided diagnosis.
abstract: Computer-aided diagnosis is a diagnostic procedure in which a radiologist uses the outputs of computer analysis of medical images as a second opinion in the interpretation of medical images, either to help with lesion detection or to help determine if the lesion is benign or malignant. Artificial neural networks (ANNs) are usually employed to formulate the statistical models for computer analysis. Receiver operating characteristic curves are used to evaluate the performance of the ANN alone, as well as the diagnostic performance of radiologists who take into account the ANN output as a second opinion. In this chapter, we use mammograms to illustrate how an ANN model is trained, tested, and evaluated, and how a radiologist should use the ANN output as a second opinion in CAD.
authors.affiliation: Radiation Oncology, City of Hope Medical Center, 1500 East Duarte Road, Duarte, CA, 91010, USA, beliu@coh.org.
authors.forename: Bei
authors.initials: B
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D001941:Breast Diseases / Q000175:diagnosis*; D003937:Diagnosis, Differential; D006801:Humans; D008327:Mammography / Q000379:methods*; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*