giRAff: an automated atlas segmentation tool adapted to single histological slices - Piluso, Sébastien; Souedet, Nicolas; Jan, Caroline; Hérard, Anne-Sophie; Clouchoux, Cédric; Delzescaux, Thierry (Frontiers in Neuroscience, 2024)
Conventional histology of the brain remains the gold standard in the analysis of animal models. In most biological studies, standard protocols usually involve the production of a limited number of histological slices to be analyzed. These slices are often selected into a specific anatomical region of interest or around a specific pathological lesion. Due to the lack of automated solutions to analyze such single slices, neurobiologists perform the segmentation of anatomical regions manually most of the time. Because the task is long, tedious and operator-dependent, we propose an automated atlas segmentation method called giRAff, combining rigid and affine registrations and suitable for conventional histological protocols involving any number of single slices from a given mouse brain. In particular, the method has been tested on several routine experimental protocols involving different anatomical regions of different sizes and for several brains. For a given set of single slices, the method is able to automatically identify the corresponding slices in the mouse Allen atlas template with a good accuracy and segmentations comparable to those of an expert. This versatile and generic method allows to segment any single slice without additional anatomical context in about one minute. Basically, our proposed giRAff method is an easy-to-use, rapid and automated atlas segmentation tool compliant with a wide variety of standard histological protocols.