Diagnosis of Vestibular Schwannoma Based on Intelligent MRI Image Processing
DOI:
https://doi.org/10.18372/1990-5548.84.20193Keywords:
vestibular schwannoma, diagnostic and prognostic biomarkers, MRI images, convolutional neural network, transformers, semantic segmentationAbstract
The study identified the main clinical and diagnostic features of the disease, reviewed modern diagnostic methods for schwannoma, including magnetic resonance imaging and computed tomography, as well as the role of clinical examination, history and laboratory tests, analyzed available open data and proposed the concept of combining medical images with molecular indicators to build more effective diagnostic models based on semantic segmentation. Diagnostic and prognostic biomarkers were summarized, including TNF-α, CD68, CD163, IL-6, CCR2 and others, which may increase the accuracy of predicting the course of the disease.
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