Automated detection of the clinically relevant image planes in a three-dimensional echocardiographic (3-DE) data set has potential applications for diagnosis of pediatric congenital heart disease. We propose a method based on template matching to automatically detect the four-chamber image plane (4CIP) in a 3-DE data set. First, a normal four-chamber image is chosen as the template. Second, to find the 4CIP in a 3-D volume, a series of cross sections are extracted from this volume. Then, a coarse-to-fine retrieval is applied to the stack of slices and the image most similar to the template is proposed as the 4CIP of this volume. We tested the method on 28 data sets of normal children and 22 data sets of children suffering from congenital heart disease, and the error rates are 7 and 9%, respectively. As will be shown, the autodetection algorithm can be straightforwardly implemented, has low computational complexity, and is robust to noise.