Automatic segmentation of newborns%26apos; skull and fontanel from CT data using model-based variational level set

作者：Jafarian Nassim; Kazemi Kamran^*; Moghaddam Hamid Abrishami; Grebe Reinhard; Fournier Marc; Helfroush Mohamad Sadegh; Gondry Jouet Catherine; Wallois Fabrice

来源：Signal, Image and Video Processing, 2014, 8(2): 377-387.

DOI：10.1007/s11760-012-0300-x

• Newborn
• CT image
• Skull
• Fontanel
• Segmentation

The newborn%26apos;s cranium is composed of flat cranial bone and fontanels forming together the envelope of the cerebral cavity. The fontanels are relatively flexible since they consist of fibrous membrane that ossifies during maturation becoming flat cranial bone as well. Fontanels give less contrast in computerized tomography (CT) images; they can be identified as gaps between the cranial bones. In this paper, we propose an automatic model-based method using variational level set to segment the skull and fontanels from CT images. In this approach, firstly a skull model consisting of cranial bones and fontanels is created and then used as constraint for level set evolution. Then, by removing the cranial bones from the segmented skulls, the fontanels are obtained. To verify the validity of the achieved results, automatically segmented skull and fontanels have been compared with the ones manually segmented by an expert using Dice similarity and Hausdorff dissimilarity measures, which show the good agreement between them. Furthermore, the surface areas of cranium and fontanel have been determined for these segmentations. The results for both, manual and automatic segmentation, are in good agreement.

• 出版日期2014-2