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IRM du cerveau néonatal : segmentation et analyse du signal

Abstract : Progress in magnetic resonance imaging (MRI) has allowed more detailed exploration of the development and maturation of the neonatal brain. Among the challenges facing radiologists are determining how best to objectively analyze images with very different characteristics when compared to older children. One issue is the “diffuse excessive high signal intensity” (DEHSI) of the white matter in premature newborns, whose definition, classification and prognosis have been vigorously debated. The role played in this analysis by the subjectivity of the radiological interpretation is not well understood. Our primary objective was to study the variability of this subjective analysis by the radiologist. Although reproducibility is acceptable for bi-dimensional measurement of brain structures, it is only fair for the analysis of signal intensity of brain white matter. The secondary objective was the design of a robust and reliable semi-automatic method to segment the gray matter, the white matter, and the cerebrospinal fluid and detect potential high signal intensity regions (it calculates a normalized mean value, and compares it to the normal surrounding white matter.). The algorithm is composed of an isotropic diffusion filter, morphological tools and connected operators, all implemented in a software interface. The results of this algorithm have been validated on MRI images acquired on 1.5 and 3 T devices by comparing them with segmentation results. This new tool could be employed in routine MRI. Correlation of the results with clinical outcomes in infants would permit a better understanding of cerebral development and, particularly, elucidate the significance of DEHSI.
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Submitted on : Thursday, January 23, 2020 - 5:15:09 PM
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  • HAL Id : tel-02453301, version 1


Baptiste Morel. IRM du cerveau néonatal : segmentation et analyse du signal. Médecine humaine et pathologie. Télécom ParisTech, 2016. Français. ⟨NNT : 2016ENST0035⟩. ⟨tel-02453301⟩



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