This paper introduces a two-steps adaptive generalized Hough transform (GHT) for the detection of non-analytic objects undergoing weak affine transformations in images. The first step of our algorithm coarsely locates the region of interest with a GHT for similitudes. The returned detection is then used by an adaptive GHT for affine transformations. The adaptive strategy makes the computation more amenable and ensures high accuracy, while keeping the size of the accumulator array small. To account for the deformable nature of natural objects, local shape variability is incorporated into the algorithm in both the detection and reconstruction steps. Finally, experiments are performed on real medical data showing that both accuracy and reasonable computation times can be reached.