{'fraction_non_alphanumeric': 0.019801980198019802, 'fraction_numerical': 0.007425742574257425, 'mean_word_length': 5.38421052631579, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Neonatal probabilistic models for brain, CSF and skull using T1-MRI data: Preliminary results

Inappropriate results may be produced if one uses adult or pediatric atlases for evaluation of neonatal cerebral images for morphological studies. This is mainly due to anatomical particularities typical for this early stage of development. In this paper, we describe the construction of a digital neonatal brain atlas from a set of images of neonates aged between 39 and 42 weeks. It consists of probabilistic models for brain, cerebrospinal fluid (CSF) and skull. In the first step, the selected images are segmented automatically followed by manual correction. In the second step, the images are normalized to a stereotaxic space defined by the neonatal brain atlas template GRAMFC_T39–42 using a popular normalization algorithm implemented in Statistical Parametric Mapping (SPM). The normalization parameters of individual subjects are then used to resample the corresponding brain, CSF and skull. Finally, to construct the probabilistic models, the average is computed for each voxel location. The atlas might be used for different applications such as source localization or neonatal structural image analysis.