Purpose: To observe the regulation of cerebral circulation in vivo based on image segmentation algorithms for deep learning in medical imaging to automatically detect and quantify the neonatal deep medullary veins (DMVs) on susceptibility weighted imaging (SWI) images. To evaluate early cerebral circulation self-rescue for neonates undergoing risk of cerebral hypoxia-ischaemia in vivo.
Methods: SWI images and clinical data of 317 neonates with or without risk of cerebral hypoxia-ischaemia were analyzed.
Background: Gliomas are the most common malignant tumors in the central nervous system originating from brain glial cells. Although characterized as highly invasive and highly malignant, few molecular targeting therapies have been developed. Ubiquitin Specific Protease 33 (USP33), a gene encoding a deubiquinating enzyme important in a variety of processes, including Slit-dependent cell migration and beta-2 adrenergic receptor signaling, participates in the development of several malignant tumors, however, its role in the development of glioma has not been evaluated.
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