UAC-Net links brain-tumor typing and MRI segmentation in one model
UAC-Net combined contextual attention and multi-scale feature fusion in a shared neural network that classified three brain-tumor types and delineated ...
UAC-Net combined contextual attention and multi-scale feature fusion in a shared neural network that classified three brain-tumor types and delineated ...
A systematic review of 123 studies maps how artificial intelligence is transforming brain imaging and computer-aided diagnosis of neurological diseases, ...
A Dutch Perspective article introduces ABI+ and calls for developmental, trans-sectoral support systems that follow children with acquired brain injury ...
A new study shows that AI-generated synthetic contrast-enhanced brain MRI images achieve impressive quality metrics but still miss critical enhancement ...
A novel MRI washout ratio separated recurrent brain tumor from radiation necrosis with an area under the curve of 0.86, ...
Mount Sinai and Johnson & Johnson will collaboratively evaluate an investigational liquid radioembolic that combines Iodine-131 with TRUFILL n-BCA to ...
A multicenter study of 104 patients finds that lower-dose and higher-dose bevacizumab produce similar radiographic outcomes in brain radiation necrosis, ...
A new review in the Journal of Translational Medicine describes how brain tumor organoid platforms are being used to reconstruct ...
A real-world study of 76 patients shows that sequencing tumor DNA in cerebrospinal fluid can diagnose mysterious brain lesions, confirm ...
A multi-center study shows that quantitative MRI radiomics features can stratify children with non-midline high-grade gliomas into risk groups with ...
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© 2025 Scienmag - Science Magazine