In this paper, we propose a framework to analyze the morphology of mouse neurons in the layer V of the cortex from 3D microscopic images. We are given 8 sets of images, each of which is composed of a 10x image showing the whole neurons, and a few (2 to 5) 40x images focusing on the somas. The framework consists in segmenting the neurons on both types of images to compute a set of specific morphological features, and in matching the neurons in the 40x images to their counterparts in the 10x images to combine the features we obtained, in a fully automatic fashion.
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