Abstract: We propose and test a wavelet transform modulus maxima method for the automated detection and extraction of coronal loops in extreme ultraviolet images of the solar corona. This method decomposes an image into a number of size scales and tracks enhanced power along each ridge corresponding to a coronal loop at each scale. We compare the results across scales and suggest the optimum set of parameters to maximize completeness, while minimizing detection of noise. For a test coronal image, we compare the global statistics (e.g. number of loops at each length) to previous automated coronal-loop detection algorithms.